Location of Repository

Neuropsychological predictors of the outcome in non-demented subjects with cognitive complaints

By 1981- Dina Lúcia Gomes da Silva


Tese de doutoramento, Ciências Biomédicas (Neurociências), Universidade de Lisboa, Faculdade de Medicina, 2012Nowadays, life expectancy has increased and gradually the prevalence of neurodegenerative disorders in the aging population began to represent a major public health problem. Alzheimer’s disease (AD) is the most common dementia and affects millions of older adults. Despite recent advances in the knowledge of AD biomarkers of pathophysiological processes, clearly the phenotype remains aetiologically heterogeneous. Understanding the clinical phenotype variation contingent to the neuropathological progression is crucial to provide intervention in the earliest phases of neurodegeneration. Newly research biomarkers have been proposed for early diagnosis of AD, however cognitive impairment remains a prominent and early feature of AD. Neuropsychological markers could offer a relatively inexpensive and noninvasive indicator of future progression to dementia because biological markers are expensive, some of them only available at few specialized centers, and, in the case of lumbar puncture, invasive. Therefore, it would not be reasonable to offer the newer and expensive biomarker techniques to all patients with cognitive complaints. Importantly, new treatments of disease modification approach require the selection of those patients with higher risk of conversion to dementia. Thus, the main goal of the present thesis was to improve the predictive value of neuropsychological measures to future conversion to dementia of patients presenting with cognitive complaints who do not fulfil the dementia criteria. Four steps were conducted in order to reach that main goal: 1. º Original published articles reporting values of sensitivity, specificity and effect sizes for neuropsychological tests to predict conversion to dementia in patients at risk of future cognitive decline were analysed in a systematic review of literature. Twenty-four studies published in the last 20 years were selected. Neuropsychological tests administered vary considerably among studies, yet the battery of tests applied generally assessed verbal memory performances, and many included also cognitive areas such as executive functions, attention and language. Methodological constrains limited the ability to provide reasonable predictive values; some studies have reported rather disparate global sensitivity and specificity rates for the neuropsychological tests to predict conversion to dementia. Conversely, other studies reported high and balanced sensitivity/specificity ratios (≥80%), mainly for verbal episodic memory tests, however the follow-up period of those studies was generally short (≈2 years). Certainly, it would be important to achieve a consensus according to the more feasible and accurate neuropsychological tests to administer for the assessment of patients at risk of conversion to dementia. On the other hand, cohort studies with longer follow-up periods would be important to propose neuropsychological tests with higher predictive accuracy and clinical relevance regarding conversion to dementia. 2. º Newer statistical classification methods derived from data mining and machine learning methods were applied to improve accuracy, sensitivity and specificity of predictors obtained from neuropsychological testing. Data used to perform the comparison of classification methods was extracted from a cohort study (CCC – Cognitive Complaints Cohort) with 775 elderly non-demented patients with cognitive complaints referred for neuropsychological evaluation. Seven non-parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press’Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Comparison of classifiers highlighted three methods more adequate to study the predictive value of neuropsychological tests in longitudinal clinical cohort studies. Support Vector Machines demonstrated the larger overall classification accuracy (Median (Me) = 0.76) and area under the ROC (Me =0.90). However, this method showed high specificity (Me = 1.0) but very low sensitivity (Me = 0.3). Random Forests ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73), specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72), specificity (Me = 0.66) and sensitivity (Me = 0.64). Results indicated the innovative data mining method of Random Forests, along with more traditional methods, namely the Linear Discriminant Analysis, should be the option in cohort studies of neuropsychological predictors of future dementia. 3. º Verbal memory is one of the first cognitive areas to decline, therefore, the predictive value of Mild Cognitive Impairment (MCI) for the conversion to dementia when using four different verbal memory tests (Logical Memory, LM; California Verbal Learning Test, CVLT; Verbal Paired-Associate Learning, VPAL; and Digit Span, DS) was analysed. Participants were consecutive patients with subjective cognitive complaints who performed a comprehensive neuropsychological evaluation and were not demented, observed in a memory clinic setting. At baseline, 272 patients from CCC reporting subjective cognitive complaints and not demented were included. During the follow-up time (3.0±1.9 years), 58 patients converted to dementia, and 214 did not. Statistically significant differences between the converters and non-converters were present in LM, VPAL and CVLT. A multivariate Cox regression analysis combining the 4 memory tests revealed that only the CVLT test remained significant as predictor of conversion to dementia. Non-demented patients with cognitive complaints diagnosed as MCI according to abnormal (< 1.5 SD) learning in the CVLT test had 3.6 higher risk of becoming demented in the follow-up. As so, the verbal memory assessment using the CVLT should be preferred in the diagnostic criteria of MCI for a more accurate prediction of conversion to dementia. 4. º The predictive value for future conversion to dementia of a comprehensive neuropsychological battery applied to a cohort of nondemented patients followed-up for 5 years was presented. Two hundred and fifty subjects were selected from CCC having cognitive complaints, assessment with a comprehensive neuropsychological battery, and follow-up of at least 5 years (if patients have not converted to dementia earlier). During the follow-up period (2.6±1.8 years for converters and 6.1±2.1 for non converters), 162 patients (64.8%) progressed to dementia (mostly Alzheimer’s disease), and 88 (35.2%) did not. A Linear Discriminant Analysis (LDA) model constituted by Digit Span backward, Semantic Fluency, Logical Memory (immediate recall) and Forgetting Index significantly discriminated converters from non-converters (λ Wilks=0.64; χ2(4)=81.95; p<0.001; RCanonical=0.60). Logical Memory (immediate recall) was the strongest predictor with a standardized canonical discriminant function coefficient of 0.70. The LDA classificatory model showed good sensitivity, specificity and accuracy values (78.8%, 79.9% and 78.6%, respectively) of the neuropsychological tests to predict long-term conversion to dementia. Results showed that it is possible to predict, on the basis of the initial clinical and neuropsychological evaluation, namely with routine tests from a comprehensive neuropsychological battery, whether non-demented patients with cognitive complaints will probably convert to dementia, or remain stable. This prediction is obtained with very good accuracy values (≈80%), similar to those reported for the newly research biomarkers, and at a reasonably long and clinically relevant term (5 years).A esperança média de vida tem vindo a aumentar e consequentemente, de modo gradual, também a prevalência de doenças neurodegenerativas, representando actualmente na população mais envelhecida um alarmante problema de saúde pública. A doença de Alzheimer é a forma mais comum de demência e afecta milhões de indivíduos adultos. Recentemente tem sido possível alcançar avanços significativos na compreensão e no conhecimento sobre os biomarcadores que traduzem os processos patofisiológicos associados à doença de Alzheimer, no entanto, é importante salientar que o fenótipo manifestado pode ainda ser de etiologia heterogénea. Compreender melhor a variação das expressões de fenótipo contigentes ao processo neuropatológico é essencial para uma identificação e intervenção mais precoce no processo neurodegenerativo. Recentemente foram propostos novos biomarcadores, ainda limitados ao âmbito da investigação, com o propósito de realizar mais cedo o diagnóstico de doença de Alzheimer. Não obstante o seu potencial, será de referir que a presença de significativas alterações cognitivas continua a ser um elemento de diagnóstico incontornável e um indicador precoce da doença de Alzheimer. Os marcadores neuropsicológicos poderão oferecer indicadores de uma futura progressão para demência que serão economicamente mais acessíveis e clinicamente menos invasivos do que a realização dos métodos necessários aos marcadores biológicos, que além de serem mais dispendiosos, apenas se encontram disponíveis em alguns centros médicos especializados e serão em alguns casos métodos invasivos (e.g., recolha de líquido cefalorraquidiano através de punção lombar). Por conseguinte, não será razoável assumir que se irá disponibilizar a todos os indivíduos com manifestas queixas subjectivas de alterações cognitivas os recentes biomarcadores, por requerem técnicas dispendiosas e/ou invasivas. Por outro lado, é importante referir que a abordagem em presente desenvolvimento para tratar a doença incidindo na modificação dos seus factores causais requer uma selecção inicial do maior número possível de indivíduos para os quais o risco de progressão para demência seja significativo. Assim sendo, o objectivo central da presente tese foi o de melhorar o valor preditivo das medidas neuropsicológicas para a determinação de uma futura progressão para demência de indivíduos com queixa de alterações cognitivas que contudo não preenchem ainda os critérios para o diagnóstico de demência. De modo a concretizar o objectivo central, quatro estudos foram desenvolvidos: 1.º - Uma revisão sistemática da literatura foi realizada com base em estudos originais publicados sobre o valor preditivo da avaliação neuropsicológica de uma futura progressão para demência, apresentando para tal os valores de sensibilidade, especificidade e magnitude do efeito para cada uma das provas neuropsicológicas. A selecção dos artigos permitiu a identificação de 24 artigos publicados nos últimos 20 anos. Os testes neuropsicológicos aplicados mudavam consideravelmente consoante o estudo em questão, contudo verificava-se que no conjunto de estudos era consistente a aplicação de provas de avaliação da memória verbal, mas também de avaliação de funções executivas, capacidade de atenção e linguagem. A presença de limitações metodológicas condicionou a potencialidade de apresentar valores preditivos razoáveis em alguns estudos, além disso, noutros estudos os valores de sensibilidade e especificidade apresentados para as provas neuropsicológicas enquanto preditoras de futura progressão para demência eram consideravelmente díspares. No entanto será importante salientar que também foi possível identificar em parte dos estudos descritos a presença de valores muito positivos e de razões equilibradas entre sensibilidade e especificidade (≥80%), principalmente para provas de avaliação da memória verbal episódica, contudo os tempos de seguimento eram na sua maioria curtos (aproximadamente 2 anos). Com certeza que seria relevante encontrar um consenso que pudesse futuramente guiar uma escolha viável e precisa das provas neuropsicológicas a aplicar para melhor predizer uma futura progressão para demência. Por outro lado, a existência de estudos de coorte longitudinais com períodos de seguimento mais alargados seria essencial para melhorar a precisão dos valores preditivos da avaliação neuropsicológica, tornando-se estes clinicamente mais relevantes no que respeita a uma futura progressão para demência. 2.º Os novos métodos de classificação estatística associados a técnicas de Prospecção de dados (em inglês data mining) e Sistemas de Aprendizagem (em inglês machine learning) foram aplicados com o intuito de melhorar a precisão, sensibilidade e especificidade dos preditores obtidos pela avaliação neuropsicológica. Para a comparação dos métodos classificatórios recorreu-se à base de dados CCC (CCC – Cognitive Complaints Cohort) que era constituída na altura por 775 casos de pacientes idosos não-dementes com queixas de alterações cognitivas e que foram referenciados para realizarem uma avaliação neuropsicológica. A comparação dos métodos estatísticos realizou-se entre 7 classificadores não-paramétricos provenientes de métodos de Prospecção de dados (Redes Neuronais com Perceptrões Multicamada; Redes Neuronais com Funções de Base Radial; Máquinas de Vectores de Suporte; CART; CHAID; Árvores de Classificação QUEST e Árvores de Classificação Aleatória) que foram comparados com três classificadores tradicionais (Análise Discriminante Linear; Análise Discriminante Quadrática, e Regressão Logística) em termos de precisão classificatória, especificidade, sensibilidade, área abaixo da curva ROC e Press’Q. O modelo para a predição consistia em 10 testes neuropsicológicos utilizados recorrentemente para o diagnóstico de demência. A comparação de classificadores identificou três métodos como os mais adequados para testar o valor preditivo dos testes neuropsicológicos em estudos longitudinais de coortes clínicas. As Máquinas de Vectores de Suporte demonstraram valores mais elevados de precisão classificatória (Mediana (Me)= 0,76) e de área abaixo da curva ROC (Me= 0,90). De salientar que, no que respeita à especificidade, este método revelou um valor elevado (Me= 1,0), contudo o valor de sensibilidade era consideravelmente baixo (Me= 0,30). As Florestas Aleatórias foram o segundo método com melhores resultados em termos de precisão (Me= 0,73), área abaixo da curva ROC (Me= 0,73), especificidade (Me= 0,73) e sensibilidade (Me= 0,64). A Análise Discriminante Linear demonstrou igualmente valores razoáveis de precisão (Me= 0,66), área abaixo da curva ROC (Me= 0,72), especificidade (Me= 0,66) e sensibilidade (Me= 0,64). Os resultados apresentados indicam que os melhores métodos classificatórios para analisar os preditores neuropsicológicos de futura progressão para demência correspondem às Florestas Aleatórias no âmbito dos mais inovadores métodos de Prospecção de dados e à Análise Discriminante Linear, enquanto método de eleição de entre os mais tradicionais para classificação de dados. 3.º A memória verbal é considerada uma das primeiras áreas cognitivas a manifestar declínio nos casos de Doença de Alzheimer. Por conseguinte, o valor preditivo de progressão para demência (Doença de Alzheimer) associado ao Defeito Cognitivo Ligeiro (DCL) foi analisado contemplando para o diagnóstico de DCL quatro testes diferentes de avaliação da memória verbal (Memória Lógica (LM); Teste de Aprendizagem Verbal de Califórnia (CVLT); Aprendizagem Verbal Associativa com Pares de Palavras (VPAL); e, Memória de Dígitos (DS)). Para o estudo foi seleccionada uma amostra consecutiva de pacientes com queixas de alterações cognitivas que em consequência das mesmas foram referenciados para realizar uma avaliação neuropsicológica pormenorizada numa clínica de memória, mas que não preenchiam ainda os critérios para o diagnóstico de demência. Uma amostra inicial de 272 pacientes com queixas cognitivas e não-dementes foram seleccionados da coorte CCC para o presente estudo. No decurso do período de seguimento (3,0±1,9 anos) ocorreu a conversão para demência em 58 pacientes, enquanto 214 permaneceram cognitivamente estáveis. Nas provas de LM, VPAL e CVLT verificaram-se diferenças estatisticamente significativas entre o grupo que converteu e o que não converteu. Através de uma análise de Regressão Multivariada de COX com um modelo constituído pelas quatro provas de memória verbal demonstrou-se que apenas a prova CVLT mantém a significância enquanto preditor de futura conversão para demência. Assim sendo, pacientes que não se encontram dementes mas que manifestam queixas de alterações cognitivas, com o diagnóstico de DCL recorrendo à pontuação na prova CVLT, se apresentarem defeito nesta prova (< 1,5 desvios-padrão abaixo da média de referência) têm um risco acrescido de evoluir para demência dentro do período de seguimento. Consequentemente, uma avaliação neuropsicológica incluindo a prova CVLT deve ser contemplada para os critérios de diagnóstico de DCL de modo a predizer com maior precisão uma futura conversão para demência. 4.º Uma coorte constituída por 250 indivíduos (seleccionados da base de dados CCC) com queixas cognitivas mas sem critérios de demência e com seguimento clínico superior a 5 anos (com excepção para os casos que evoluíram para demência antes dos 5 anos) foi analisada com vista à determinação do valor preditivo dos testes neuropsicológicos a longo prazo. Durante o período de seguimento (2,6±1,8 anos para os indivíduos que evoluíram para demência e 6,1±2,1 anos para os que permaneceram estáveis a nível cognitivo) 162 indivíduos (64,8%) apresentaram os critérios para o diagnóstico de demência (principalmente para Doença de Alzheimer), enquanto que 88 (35,2%) permaneceram estáveis. Foi possível discriminar entre os indivíduos que progrediram para demência e os que permaneceram estáveis através de um modelo de Análise Discriminante Linear (ADL) com os resultados iniciais da avaliação nas provas: Memória de Dígitos inversa, Fluência Semântica, Memória Lógica (evocação imediata), e o Índice de Esquecimento da Memória Lógica (λ Wilks= 0,64; χ2 (4)= 81,95; p< 0,001; RCanonical= 0,60). O preditor neuropsicológico mais robusto, com coeficiente estandardizado da função discriminante (canónica) de 0,70, foi a prova de Memória Lógica (evocação imediata). O modelo classificatório da ADL demonstrou valores muito positivos para a sensibilidade, especificidade e precisão classificatória (78,8%, 79,9% e 78,6%, respectivamente), dos testes neuropsicológicos para predizer uma futura progressão para demência a longo prazo. Os resultados apresentados evidenciam a possibilidade de predizer, com base numa avaliação inicial, clínica e neuropsicológica, com uma bateria de provas cognitivas aplicada na rotina clínica, se o indivíduo que apresenta queixas cognitivas irá evoluir para demência ou permanecer estável nos próximos anos. Será de salientar que o valor preditivo foi obtido com uma precisão bastante aceitável (≈ 80%), na ordem dos valores obtidos para os biomarcadores mais recentes, e no âmbito de um período de seguimento consideravelmente longo e portanto clinicamente relevante (5 anos)

Topics: Teses de doutoramento - 2012, Neuropsicologia, Demência, Doença de Alzheimer, Neurociências
Year: 2012
OAI identifier: oai:repositorio.ul.pt:10451/7503

Suggested articles



  1. (2012). (volume and pages numbers not reported by publisher). doi
  2. (2006). [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology doi
  3. (2000). A brief cognitive test battery to differentiate Alzheimer’s disease and frontotemporal dementia. Neurology doi
  4. (2007). A comparison of regression trees, logistic regression, generalized additive models, and multivariate adaptive regression splines for predicting AMI mortality. Stat Med doi
  5. (2011). A comparison of screening tools for the assessment of Mild Cognitive Impairment: Preliminary findings. Neurocase doi
  6. (2009). A comparison study of mild cognitive impairment with 3 memory tests among Chinese individuals. Alzheimer Dis Assoc Disord doi
  7. (2009). A gamma secretase inhibitor decreases amyloid-beta production in the central nervous system. Ann Neurol doi
  8. (1999). A historical review of the concept of vascular dementia: lessons from the past for the future. Alzheimer Dis Assoc Disord doi
  9. (2012). A longitudinal study of semantic memory impairment in patients with Alzheimer's disease. doi
  10. (2002). A review of evidence of health benefit from artificial neural networks in medical intervention. Neural Netw doi
  11. (1998). A Tutorial on Support Vector Machines for Pattern Recognition. Data Min Knowl Discov
  12. (1994). A validation study of the Dementia Questionnaire. Arch Neurol doi
  13. (2010). Advances in quantitative magnetic resonance imaging-based biomarkers for Alzheimer disease. Alzheimers Res Ther doi
  14. Advantages and disadvantages of neural networks for predicting clinical outcomes. doi
  15. (2012). Age and diagnostic performance of Alzheimer disease CSF biomarkers. Neurology doi
  16. (2001). Age-dependent changes in brain, CSF, and plasma amyloid (beta) protein in the Tg2576 transgenic mouse model of Alzheimer’s disease.
  17. (2000). Age-related cognitive decline, mild cognitive impairment or preclinical Alzheimer’s disease? Ann Med doi
  18. (2007). Aliferis CF. Are random forests better than support vector machines for microarray-based cancer classification? AMIA Annu Symp Proc
  19. (2007). Alternate forms of logical memory and verbal fluency tasks for repeated testing in early cognitive changes. Int Psychogeriatr doi
  20. (2011). Alzheimer and his disease: a brief history. Neurol Sci doi
  21. (2012). Alzheimer Disease Neuroimaging Initiative FT. Comparison of imaging biomarkers in the Alzheimer disease neuroimaging initiative and the mayo clinic study of aging.
  22. (2009). Alzheimer's Disease Neuroimaging Initiative. Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects. Ann Neurol doi
  23. Alzheimer's Disease Neuroimaging Initiative. Longitudinal change of biomarkers in cognitive decline. Arch Neurol 2011; 68(10): 1257-1266. Neuropsychological predictors of the outcome in non-demented subjects with cognitive complaints
  24. (2012). Alzheimer's Disease Neuroimaging Initiative. Predicting Future Clinical Changes of MCI Patients Using Longitudinal and Multimodal Biomarkers. PLoS One doi
  25. (2011). Alzheimer's Disease Neuroimaging Initiative. The dynamics of cortical and hippocampal atrophy in Alzheimer disease. Arch Neurol
  26. (2010). Alzheimer’s Disease Neuroimaging Initiative. Clinical Core of the Alzheimer’s Disease Neuroimaging Initiative: progress and plans. Alzheimers Dement doi
  27. (2011). Alzheimer’s Disease Neuroimaging Initiative. Derivation of a new ADAS-cog composite using tree-based multivariate analysis: prediction of conversion from mild cognitive impairment to Alzheimer disease. Alzheimer Dis Assoc Disord doi
  28. (2010). AM; Alzheimer's Disease Neuroimaging Initiative. Brain substrates of learning and retention in mild cognitive impairment diagnosis and progression to Alzheimer's disease. Neuropsychologia doi
  29. (2012). American Alzheimer's Disease Neuroimaging Initiative (ADNI). Prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia based upon biomarkers and neuropsychological test performance. Neurobiol Aging doi
  30. (2004). Amnestic MCI or prodromal Alzheimer’s disease? Lancet Neurol doi
  31. (2006). Amnestic mild cognitive impairment: diagnostic outcomes and clinical prediction over a two-year time period. doi
  32. (2007). Amnestic syndrome of the medial temporal type identifies prodromal AD - A longitudinal study. Neurology doi
  33. (2011). Amyloid imaging as a biomarker for cerebral β-amyloidosis and risk prediction for Alzheimer dementia. Neurobiol Aging doi
  34. (2010). Amyloid-beta(1-42), total tau, and phosphorylated tau as cerebrospinal fluid biomarkers for the diagnosis of Alzheimer disease. Clin Chem doi
  35. (1980). An exploratory technique for investigation large quantities of categorical data Applied Statistics doi
  36. (2004). and biochemical spectrum of Alzheimer disease associated with PS-1 mutations.
  37. (1997). and mild cognitive impairment. Int Psychogeriatr doi
  38. (2005). Annual conversion to Alzheimer disease among patients with memory complaints attending an outpatient memory clinic: The influence of amnestic mild cognitive impairment and the predictive value of neuropsychological testing. doi
  39. (2004). Annual rate and predictors of conversion to dementia in subjects presenting mild cognitive impairment criteria defined according to a population-based study. Dement Geriatr Cogn Disord doi
  40. (2011). Anomia as a marker of distinct semantic memory impairments in Alzheimer's disease and semantic dementia. Neuropsychology doi
  41. (1995). Apolipoprotein E status as a predictor of the development of Alzheimer's disease in memory-impaired individuals.
  42. (2007). Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG). doi
  43. (2007). Applications of Support Vector Machines in Chemistry. doi
  44. (2000). Applied logistic regression. 2 Edition. doi
  45. (2012). Assessing Candidate Serum Biomarkers for Alzheimer's Disease: A Longitudinal Study.
  46. (2007). Assessment of the performances of multilayer perceptron neural networks in comparison with recurrent neural networks and two statistical methods for diagnosing coronary artery disease. Expert Systems doi
  47. (2006). Association between CSF biomarkers and incipient Alzheimer's disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol doi
  48. (1968). Association between quantitative measures of dementing and senile change in cerebral grey matter of elderly subjects. doi
  49. (2000). Association. Diagnostic and statistical manual of mental disorders. 4th Edition, Text Revision. doi
  50. (1992). Atrophy of medial temporal lobes on MRI in &quot;probable&quot; Alzheimer's disease and normal ageing: diagnostic value and neuropsychological correlates. doi
  51. (2005). Attention and executive control predict Alzheimer disease in late life: results from the Berlin Aging Study (BASE).
  52. (1984). attention, and functional status in community-residing Alzheimer type dementia patients and optimally healthy aged individuals. doi
  53. (1997). Auguste D and Alzheimer's disease. Lancet doi
  54. (2007). Beta-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer’s disease. Brain doi
  55. (2002). Biological markers in Alzheimer disease.
  56. (2012). Biomarker validation of a cued recall memory deficit in prodromal Alzheimer disease. Neurology doi
  57. (1999). Biomarkers of Alzheimer disease. doi
  58. (2009). Biomarkers of Alzheimer's disease. Neurobiol Dis doi
  59. (2008). Blessed Dementia Rating Scale (BDRS). doi
  60. (2010). Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease. doi
  61. (1986). CAMDEX: a standardized instrument for the diagnosis of mental disorders in the elderly with special reference to early detection of dementia. doi
  62. (2006). Cases with mild cognitive impairment and Alzheimer’s disease fail to benefit from repeated exposure to episodic memory tests as compared with controls. doi
  63. (2011). Category cued recall following controlled encoding as a neuropsychological tool in the diagnosis of Alzheimer’s disease: a review of the evidence. Neuropsychol Rev doi
  64. (2009). Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol doi
  65. (1999). Cerebrospinal fluid tau protein shows a better discrimination in young old (<70 years) than in old old patients with Alzheimer's disease compared with controls. Neurosci Lett doi
  66. (2007). Cerebrospinal Fluid tau/beta-Amyloid42 Ratio as a Prediction of Cognitive Decline in Nondemented Older Adults. Arch Neurol doi
  67. (2012). Changes in mild cognitive impairment and its subtypes as seen on diffusion tensor imaging. Int Psychogeriatr doi
  68. (2008). Characterizing the memory changes in persons with mild cognitive impairment. Prog Brain Res doi
  69. (2007). Classification Accuracy of Neural Networks vs. Discriminant Analysis, Logistic Regression, and Classification and Regression Trees: Three- and Five-Group Cases. Methodology doi
  70. (2002). Classification and Regression by random Forest.
  71. (2003). Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression. Ann Behav Med doi
  72. (1984). Classification and regression trees. doi
  73. (2007). Classification of patients with pain based on neuropathic pain symptoms: Comparison of an artificial neural network against an established scoring system. doi
  74. (2010). Clinical and biological predictors of Alzheimer's disease in patients with amnestic mild cognitive impairment. Rev Bras Psiquiatr doi
  75. (1993). Clinical Dementia Rating (CDR): current version and scoring rules. Neurology doi
  76. (1984). Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA doi
  77. (2007). Clinical prediction of Alzheimer disease dementia across the spectrum of mild cognitive impairment. Arch Gen Psychiatry doi
  78. (1998). Clinical subtypes of Alzheimer's disease. Dement Geriatr Cogn Disord doi
  79. (2006). Clinical trials in mild cognitive impairment: lessons for the future. doi
  80. (1994). Clock-drawing: a neuropsychological analysis. NY: doi
  81. (1996). Cognitive and neurobiologic markers of early Alzheimer disease. doi
  82. (2011). Cognitive decline in prodromal Alzheimer disease and mild cognitive impairment. Arch Neurol doi
  83. (2006). Cognitive measures predict pathologic Alzheimer disease. Arch Neurol doi
  84. (1997). Cognitive predictors of incident Alzheimer's disease: a prospective longitudinal study. Neuropsychology doi
  85. (1998). Cognitive process in preclinical phase of dementia.
  86. (2000). Cognitive tests that best discriminate between presymptomatic AD and those who remain nondemented. Neurology doi
  87. (2009). Colliot O; Alzheimer's Disease Neuroimaging Initiative. Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging. Neuroimage doi
  88. (2008). Combining early markers strongly predicts conversion from mild cognitive impairment to Alzheimer's disease. Biol Psychiatry doi
  89. (1999). Comparative MR analysis of the entorhinal cortex and hippocampus in diagnosing Alzheimer disease.
  90. (1995). Comparing classification accuracy of neural networks, binary logit regression and discriminant analysis for insolvency prediction of life insurers. doi
  91. (1999). Comparing linear discriminant function with logistic regression for the two-group classification problem. doi
  92. (2008). Comparing performances of logistic regression, classification and regression tree, and neural networks for predicting coronary artery disease. Expert Syst Appl doi
  93. (2006). Comparison between neural networks and multiple logistic regression to predict acute coronary syndrome in the emergency room. Artif Intell Med doi
  94. (2012). Comparison of Four Verbal Memory Tests for the Diagnosis and Predictive Value of Mild Cognitive Impairment. Dement Geriatr Cogn Disord Extra doi
  95. (2004). Comparison of Logistic Regression and Linear. Discriminant Analysis: A Simulation Study. Metodološki zvezki
  96. (2003). Comparison of the short test of mental status and the mini-mental state examination in mild cognitive impairment. Arch Neurol doi
  97. (2005). Comparison of three statistical classifiers on a prostate cancer data. Neural Netw World
  98. (2010). Comparison of verbal memory impairment rates in mild cognitive impairment. doi
  99. (1998). Contributo da Neuropsicologia para o Estudo das Demências. Dissertação de Doutoramento em Ciências Biomédicas, Faculdade de Medicina de
  100. (2004). Conversion from subtypes of mild cognitive impairment to Alzheimer dementia. Neurology 2007; 69: 409. Neuropsychological predictors of the outcome in non-demented subjects with cognitive complaints doi
  101. (2007). Conversion of amnestic Mild Cognitive Impairment to dementia of Alzheimer type is independent to memory deterioration. doi
  102. (2009). CSF biomarker levels in early and late onset Alzheimer's disease. Neurobiol Aging doi
  103. (2009). CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA doi
  104. (1984). Cued-recall in amnesia. doi
  105. (2001). Current concepts in mild cognitive impairment. Arch Neurol doi
  106. (2011). Data mining methods in the prediction of dementia: a realdata comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests. doi
  107. (2004). Deficient acquisition and consolidation: intertrial free recall performance in Alzheimer’s disease and mild cognitive impairment. doi
  108. (2012). Defining Alzheimer as a common age-related neurodegenerative process not inevitably leading to dementia. Prog Neurobiol doi
  109. (2010). Defining mild cognitive impairment: impact of varying decision criteria on neuropsychological diagnostic frequencies and correlates.
  110. (1986). Dementia and working memory. doi
  111. (1986). Dementia of the Alzheimer type. An inventory of diagnostic clinical features.
  112. (2010). Dementia risk prediction in the population: are screening models accurate? Nat Rev Neurol doi
  113. (2010). Detecting prodromal Alzheimer’s disease in mild cognitive impairment: utility of the CAMCOG and other neuropsychological predictors. doi
  114. (2007). Detection of memory impairment in the general population: screening by questionnaire and telephone compared to subsequent face-to-face assessment. doi
  115. (1983). Development and validation of a geriatric depression screening scale: a preliminary report. doi
  116. (2002). Differential diagnosis of Alzheimer disease with cerebrospinal fluid levels of tau protein phosphorylated at threonine 231. Arch Neurol doi
  117. (2000). Differential impact of executive dysfunction on verbal list learning and story recall. Clin Neuropsychol doi
  118. (2009). Differential memory test sensitivity for diagnosing amnestic mild cognitive impairment and predicting conversion to Alzheimer's disease. doi
  119. (2004). Discriminant analysis and statistical pattern recornition. London: Wiley Interscience,
  120. (1984). Doença de Alzheimer, problemas do diagnóstico clínico. Tese de Doutoramento. Faculdade de Medicina de Lisboa,
  121. (2011). Early detection of Alzheimer disease: C-PiB PET in twins discordant for cognitive impairment. Neurology doi
  122. (2007). Early Diagnosis Group of the Italian Interdisciplinary Network on Alzheimer’s Disease. Amnestic mild cognitive impairment: difference of memory profile in subjects who converted or did not convert to Alzheimer’s disease. Neuropsychology doi
  123. (2005). Early Diagnosis Group of the Italian Interdisciplinary Network on Alzheimer’s Disease. Characterization of memory profile in subjects with amnestic mild cognitive impairment. doi
  124. (2010). Early-onset Alzheimer disease: the contribution of neuroimaging for the diagnosis. Psychiatry Res doi
  125. (2003). Educ
  126. (1984). Effects of aging and dementia upon recent visuospatial memory. Neurobiol Aging doi
  127. (1989). Effects of Sample Size in Classifier Design. doi
  128. (2011). Effects of varying diagnostic criteria on prevalence of mild cognitive impairment in a community based sample. J Alzheimers Dis
  129. (2004). Efficient training of RBF networks for classification. doi
  130. (2008). Episodic memory and speed/attention deficits are associated with Alzheimer-typical CSF abnormalities in MCI. doi
  131. (2011). Evaluation of a calibrated (18)F-FDG PET score as a biomarker for progression in Alzheimer disease and mild cognitive impairment. doi
  132. (2001). Evaluation of CSF-tau and CSFAbeta42 as diagnostic markers for Alzheimer disease in clinical practice. Arch Neurol doi
  133. (1998). Evolution in the Conceptualization of Dementia and Alzheimer’s Disease: Greco-Roman Period to the 1960s. Neurobiology of Aging doi
  134. (2012). Executive Dysfunction in MCI: Subtype or Early Symptom. doi
  135. (1995). Executive function deficits in mild Alzheimer’s disease. Neuropsychology doi
  136. (2010). Feature selection and performance evaluation of support vector machine (SVM)-based classifier for differentiating benign and malignant pulmonary nodules by computed tomography. doi
  137. (2003). fMRI studies of associative encoding in young and elderly controls and mild Alzheimer’s disease.
  138. (2008). Follow-Up of Mild Cognitive Impairment and Related Disorders over Four Years in Adults in Their Sixties: The PATH Through Life Study. Dement Geriatr Cogn Disord doi
  139. (2012). for the Alzheimer’s Disease Neuroimaging Initiative. Longitudinal change in neuropsychological performance using latent growth models: a study of mild cognitive impairment. Brain Imaging Behav doi
  140. (2010). Free and cued selective reminding identifies very mild dementia in primary care. Alzheimer Dis Assoc Disord doi
  141. (2008). Frequency and course of mild cognitive impairment in a multiethnic community. Ann Neurol doi
  142. (1987). Genuine memory deficit in dementia. doi
  143. (1986). Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. doi
  144. (2008). Geriatric Depression Scale (GDS).
  145. (2005). Global prevalence of dementia: a Delphi consensus study. Lancet Neurol doi
  146. (2007). Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease. Neurology doi
  147. (2001). Hippocampal formation glucose metabolism and volume losses in MCI and AD. Neurobiol Aging doi
  148. (2004). Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol Aging doi
  149. (1998). History of dementia and dementia in history: an overview. doi
  150. (1992). Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol 2010; 9: 119-128. (a) Jack CR Jr, Petersen RC, O'Brien PC, Tangalos EG. MR-based hippocampal volumetry in the diagnosis of Alzheimer's disease. Neurology
  151. (2003). Identification of new presenilin gene mutations in early-onset familial Alzheimer disease. Arch Neurol doi
  152. (2011). Identifying and Characterizing Trajectories of Cognitive Change in Older Persons with Mild Cognitive Impairment. Dement Geriatr Cogn Disord doi
  153. (2004). Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann Neurol doi
  154. (2007). Imaging of mild cognitive impairment and early dementia. doi
  155. (2007). Imaging β-amyloid burden in aging and dementia. Neurology doi
  156. (2011). Impaired digit span can predict further cognitive decline in older people with subjective memory complaint: a preliminary result. Aging Ment Health doi
  157. (1999). Improved discrimination of AD patients using beta-amyloid (1–42) and tau levels in CSF. Neurology doi
  158. (2004). Improvements in Personnel Selection with Neural Nets: A Pilot Study in the field of Aviation Psychology. doi
  159. (2008). Increasing CSF phospho-tau levels during cognitive decline and progression to dementia. Neurobiol Aging doi
  160. (1994). Initial letter and semantic category fluency in Alzheimer's disease, Huntington's disease, and progressive supranuclear palsy. doi
  161. (2012). Injury markers but not amyloid markers are associated with rapid progression from mild cognitive impairment to dementia in Alzheimer's disease.
  162. (2009). Investigators. Functional and cognitive criteria produce different rates of mild cognitive impairment and conversion to dementia. doi
  163. (2010). Is brain amyloid production a cause or a result of dementia of the Alzheimer's type? J Alzheimers Dis
  164. (2009). Jagust WJ; Alzheimer's Disease Neuroimaging Initiative. Episodic memory loss is related to hippocampal mediated beta-amyloid deposition in elderly subjects. doi
  165. (2008). Language performance in Alzheimer's disease and mild cognitive impairment: A comparative review. doi
  166. (2007). Lexical semantic memory in amnestic mild cognitive impairment and mild Alzheimer’s disease. Arq Neuropsiquiatr doi
  167. (2007). LJ; Alzheimer’s Disease Cooperative study. Clinical predictors of progression to Alzheimer disease in amnestic mild cognitive impairment. Neurology doi
  168. (2012). Longitudinal Cerebrospinal Fluid Biomarkers over Four Years in Mild Cognitive Impairment. doi
  169. (2011). Longitudinal patterns of β-amyloid deposition in nondemented older adults. Arch Neurol doi
  170. (1990). Longitudinal study of cerebral metabolic asymmetries and associated neuropsychological patterns in early dementia of the Alzheimer type. Arch Neurol doi
  171. (2009). Longitudinal study of the transition from healthy aging to Alzheimer disease. Arch Neurol doi
  172. (2011). Lyketsos CG. Progression of cognitive, functional, and neuropsychiatric symptom domains in a population cohort with Alzheimer dementia: the Cache County Dementia Progression study. doi
  173. (2001). Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer's disease.
  174. (1981). Manual for the Wechsler Adult Intelligence Scale—Revised. doi
  175. (2009). Medial temporal lobe atrophy on MRI differentiates Alzheimer's disease from dementia with Lewy bodies and vascular cognitive impairment: a prospective study with pathological verification of diagnosis. Brain doi
  176. (2004). Medial temporal lobe atrophy on MRI predicts dementia in patients with mild cognitive impairment. Neurology doi
  177. (2008). Medial temporal lobe atrophy on MRI scans and the diagnosis of Alzheimer disease. Neurology doi
  178. (2008). Medical Research Council Cognitive Function and Ageing Study. Two-year progression from mild cognitive impairment to dementia: to what extent do different definitions agree? J Am Geriatr Soc doi
  179. (1995). Memory disorders in probable Alzheimer’s disease: the role of hippocampal atrophy as shown with MRI. doi
  180. (1994). Memory function in very early Alzheimer’s disease. Neurology doi
  181. (2008). Memory impairment, executive dysfunction, and intellectual decline in preclinical Alzheimer’s disease. doi
  182. (2008). Memory profiling with paired associate learning in Alzheimer’s disease, mild cognitive impairment, and healthy aging. Neuropsychology doi
  183. (2004). Mild cognitive impairment - Focus on diagnosis. doi
  184. (2004). Mild cognitive impairment – beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. doi
  185. (2007). Mild cognitive impairment and cognitive impairment, no dementia: part A, concept and diagnosis. Alzheimers Dement doi
  186. (2008). Mild cognitive impairment as predictor for Alzheimer’s disease in clinical practice: effect of age and diagnostic criteria. Psychol Med doi
  187. (1991). Mild cognitive impairment in the elderly: predictors of dementia. Neurology doi
  188. (1998). Mild cognitive impairment-an early stage of Alzheimer’s disease? doi
  189. (2004). Mild cognitive impairment: a cross-national comparison.
  190. (2008). Mild cognitive impairment: a risk indicator of later dementia, or a preclinical phase of the disease? doi
  191. (2003). Mild cognitive impairment: aging to Alzheimer’s disease. doi
  192. (2004). Mild cognitive impairment: an epidemiologic perspective. Dialogues Clin Neurosc
  193. (1999). Mild cognitive impairment: clinical characterization and outcome. Arch Neurol doi
  194. (2006). Mild cognitive impairment: deficits in cognitive domains other than memory. Dement Geriatr Cogn Disord doi
  195. (2003). Mild cognitive impairment: prevalence and incidence according to different diagnostic criteria. doi
  196. (1975). Mini-mental state’: a practical method for grading the cognitive state of patients for the clinician. doi
  197. (2006). Misclassification Rates for Four Methods of Group Classification: Impact of Predictor Distribution, Covariance Inequality, Effect Size, Sample Size, and Group Size Ratio. Educ Psychol Meas doi
  198. (2011). Montreal Cognitive Assessment: Validation Study for Mild Cognitive Impairment and Alzheimer Disease. Alzheimer Dis Assoc Disord doi
  199. (2012). MRI hippocampal and entorhinal cortex mapping in predicting conversion to Alzheimer's disease. Neuroimage doi
  200. (1976). Multilingual Aphasia Examination.
  201. (2008). Multiplexed quantification of dementia biomarkers in the CSF of patients with early dementias and MCI: a multicenter study. Neurobiol Aging doi
  202. (2002). Natural history of mild cognitive impairment in older persons. Neurology doi
  203. (1996). Neural networks and logistic regression. Part II. Comput Stat Data Anal doi
  204. (1995). Neural Networks for Pattern Recognition. doi
  205. (2010). Neural networks.
  206. (2011). Neuropathological alterations in Alzheimer disease. Cold Spring Harb Perspect Med doi
  207. (1995). Neuropsychological assessment (3rd ed.). doi
  208. (1991). Neuropsychological assessment in Alzheimer’s disease. Exp Aging Res
  209. (1991). Neuropsychological assessment in clinical trials of Alzheimer disease. Alzheimer Dis Assoc Disord doi
  210. (2006). Neuropsychological characteristics of mild cognitive impairment subgroups. doi
  211. (2007). Neuropsychological impairment in the early Alzheimer’s disease. Encephale
  212. (2007). Neuropsychological measures in normal individuals that predict subsequent cognitive decline. Arch Neurol doi
  213. (2006). Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment. Arch Gen Psychiatry doi
  214. (2003). Neuropsychological prediction of conversion to dementia from questionable dementia: statistically significant but not yet clinically useful. doi
  215. (1999). Neuropsychological prediction of decline to dementia in nondemented elderly. doi
  216. (2010). Neuropsychological predictors of rapidly progressing patients with Alzheimer's disease. Dement Geriatr Cogn Disord doi
  217. (2005). Neuropsychological tests accurately predict incident Alzheimer disease after 5 and 10 years. Neurology doi
  218. (2009). Norms for change in episodic memory as a prerequisite for the diagnosis of mild cognitive impairment (MCI). Neuropsychology doi
  219. (2012). Not quite PIB-positive, not quite PIBnegative: slight PIB elevations in elderly normal control subjects are biologically relevant. Neuroimage doi
  220. (2005). Novel mutations and repeated findings of mutations in familial Alzheimer disease. Neurogenetics doi
  221. (2007). Novel panel of cerebrospinal fluid biomarkers for the prediction of progression to Alzheimer dementia in patients with mild cognitive impairment. Arch Neurol doi
  222. (2000). Novel presenilin 1 mutations associated with early onset of dementia in a family with both early-onset and late-onset Alzheimer disease. Arch Neurol doi
  223. (2000). On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology. Stat Med doi
  224. (2011). Optimizing the CAMCOG test in the screening for mild cognitive impairment and incipient dementia: saving time with relevant domains. doi
  225. (1992). Organisation. doi
  226. (2009). Outcome in subgroups of mild cognitive impairment (MCI) is highly predictable using a simple algorithm. doi
  227. (2001). Pathophysiology of Alzheimer syndrome.
  228. (2010). Patterns of cognitive decline, conversion rates, and predictive validity for 3 models of MCI. doi
  229. (2011). Patterns of deficits in daily functioning and cognitive performance of patients with Alzheimer disease. doi
  230. (2006). Patterns of verbal memory performance in mild cognitive impairment, Alzheimer disease, and normal aging. Cogn Behav Neurol doi
  231. (2009). Persistence of neuropsychological testing deficits in mild cognitive impairment. Dement Geriatr Cogn Disord doi
  232. (2008). PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging doi
  233. (1999). Phonological loop and central executive functioning in Alzheimer’s disease. Neuropsychologia
  234. (2009). PM; Alzheimer's Disease Neuroimaging Initiative. Alzheimer's disease neuroimaging initiative: a one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition. Neuroimage doi
  235. (2008). Potential for misclassification of mild cognitive impairment: a study of memory scores on the Wechsler Memory Scale-III in healthy older adults. doi
  236. (2001). Practice parameter: early detection of dementia: mild cognitive impairment (an evidence-based review). doi
  237. (2004). Preclinical Alzheimer disease: neuropsychological test performance 1.5 to 8 years prior to onset. Neurology doi
  238. (2005). Preclinical Alzheimer's disease: diagnosis and prediction of progression. Lancet Neurol doi
  239. (2007). Preclinical dementia: an Italian multicentre study on amnestic mild cognitive impairment. Dement Geriatr Cogn Disord doi
  240. (2001). Preclinical prediction of AD using neuropsychological tests. doi
  241. (2010). Predicting outcome in mild cognitive impairment: 4-year follow-up study. doi
  242. (2008). Predicting rapid clinical progression in amnestic mild cognitive impairment. Dement Geriatr Cogn Disord doi
  243. (2000). Prediction of probable Alzheimer disease in patients with symptoms suggestive of memory impairment. Value of the Mini-Mental State Examination. Arch Fam Med doi
  244. (2010). Prefrontal compensatory mechanism may enable normal semantic memory performance in mild cognitive impairment (MCI). doi
  245. (2009). Prevalence of mild cognitive impairment and its subtypes are influenced by the application of diagnostic criteria: results from the Korean Longitudinal Study on Health and Aging (KLoSHA). Dement Geriatr Cogn Disord doi
  246. (2008). Prodromal Alzheimer's disease: successive emergence of clinical symptoms. Ann Neurol doi
  247. (1991). Profiles of demented and amnesic patients on the California verbal learning test: Implications for the assessment of memory disorders. Psychol Assessment doi
  248. (2007). Profiles of neuropsychological impairment in autopsy-defined Alzheimer's disease and cerebrovascular disease. doi
  249. (2007). Progressive impairment on neuropsychological tasks in a longitudinal study of preclinical Alzheimer's disease. Neuropsychology doi
  250. (2006). Promoter mutations that increase amyloid precursor-protein expression are associated with Alzheimer disease. doi
  251. (2012). Proteomic changes in cerebrospinal fluid of presymptomatic and affected persons carrying familial Alzheimer disease mutations. Arch Neurol doi
  252. (1986). Prueba perceptiva y de atención. Tea Ediciones –
  253. (1984). Psychometric differentiation of mild senile dementia of the Alzheimer type. Arch Neurol doi
  254. (2009). Quantification of five neuropsychological approaches to defining mild cognitive impairment.
  255. (1997). Questionable dementia: clinical course and predictors of outcome. doi
  256. (2008). Radial basis function neural networks classification for the recognition of idiopathic pulmonary fibrosis in microscopic images. doi
  257. (2001). Random forests. doi
  258. (2001). RBF network classification of ECGs as a potential marker for sudden cardiac death In RBF network classification of ECGs as a potential marker for sudden cardiac death Physica-Verlag GmbH doi
  259. (1991). Recent studies on dementia senilis and brain disorders caused by atheromatous vascular disease: by A. Alzheimer, 1898. Alz Dis Assoc Dis doi
  260. (2008). Recollection and familiarity in amnestic mild cognitive impairment: a global decline in recognition memory. Neuropsychologia doi
  261. (1998). Redes neurales vs modelos estadísticos: Simulaciones sobre tareas de predicción y clasificación. Psicológica
  262. (2007). Reinvang I. APOE status and its association to learning and memory performance in middle aged and older Norwegians seeking assessment for memory deficits. Behav Brain Funct doi
  263. (2000). Relationship between functional and neuropsychological performance in early Alzheimer disease. Alzheimer Dis Assoc Disord doi
  264. (2002). Relationships among cerebrospinal fluid biomarkers in dementia of the Alzheimer type. Alzheimer Dis Assoc Disord doi
  265. (2010). Report of the Alzheimer’s Disease Dementia Workgroup. Released at: The Alzheimer's Association International Conference, doi
  266. (1996). Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 2007; 6: 734-746 Duin RPW. A note on comparing classifiers. Pattern Recognition Letters doi
  267. (2006). Revised criteria for mild cognitive impairment: validation within a longitudinal population study. Dement Geriatr Cogn Disord doi
  268. (2008). Robust and conventional neuropsychological norms: diagnosis and prediction of age-related cognitive decline. Neuropsychology doi
  269. (2007). Scheltens P; Alzheimer's Disease Cooperative Study Group. Qualitative estimates of medial temporal atrophy as a predictor of progression from mild cognitive impairment to dementia. Arch Neurol
  270. (2012). Screening utility of the Montreal Cognitive Assessment (MoCA): in place of-or as well as-the MMSE? Int Psychogeriatr doi
  271. (1999). Sensitivity to semantic cuing: an index of episodic memory dysfunction in early Alzheimer disease. Alzheimer Dis Assoc Disord doi
  272. (1999). Short versions of the geriatric depression scale: a study of their validity for the diagnosis of a major depressive episode according to ICD-10 and DSM-IV. doi
  273. (1991). Small Sample Size Effects in Statistical Pattern Recognition: Recommendations for Practitioners. doi
  274. (1997). Specific hippocampal volume reductions in individuals at risk for Alzheimer's disease. Neurobiol Aging doi
  275. (1997). Split selection methods for classification trees. Statistica Sinica
  276. (1996). St George-Hyslop PH. Prediction of probable Alzheimer's disease in memory-impaired patients: A prospective longitudinal study. Neurology doi
  277. (1995). Staging of Alzheimer's disease-related neurofibrillary changes. Neurobiol Aging doi
  278. (2012). Staging of the cognitive decline in Alzheimer's disease: insights from a detailed neuropsychological investigation of mild cognitive impairment and mild Alzheimer's disease. doi
  279. (2004). Subtle memory decline over 12 months in mild cognitive impairment. Dement Geriatr Cogn Disord doi
  280. (2006). Support Vector Machines in R.
  281. (2000). Support vector machines: Hype or hallelujah? SIGKDD Explorations doi
  282. (1995). Support-Vector Networks. doi
  283. (2007). Symptoms of Memory Loss as Predictors of Cognitive Impairment? The Use and Reliability of Memory Ratings in a Clinic Population. Alzheimer Dis Assoc Disord doi
  284. (1995). Tau protein in cerebrospinal fluid: a biochemical marker for axonal degeneration in Alzheimer disease? Mol Chem Neuropathol doi
  285. (2010). Tau-proteins as gender-specific state markers in amnestic mild cognitive impairment. Dement Geriatr Cogn Disord doi
  286. (2006). Ten-year risk of dementia in subjects with mild cognitive impairment. Neurology doi
  287. (2000). Test de Toulouse-Pieron aplicado a jugadores de fútbol profesional Club El Porvenir, años 1996/98.
  288. (1995). The “preclinical phase” of probable Alzheimer’s disease. Arch Neurol
  289. (2006). The Addenbrooke's Cognitive Examination Revised (ACE-R): a brief cognitive test battery for dementia screening. doi
  290. (2010). The California Verbal Learning Test and other standard clinical neuropsychological tests to predict conversion from mild memory impairment to dementia. doi
  291. (1987). The California Verbal Learning Test: Research Edition Adult Version. The Psychological Corporation, doi
  292. (2000). The course of cognitive impairment in preclinical Alzheimer disease: three- and 6-year follow-up of a population-based sample. Arch Neurol doi
  293. (1991). The decline of working memory in Alzheimer’s disease. A longitudinal study. doi
  294. (2011). The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement doi
  295. (2011). The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement doi
  296. (2007). The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis. J Am Stat Assoc 1975; 70: 892-898. Neuropsychological predictors of the outcome in non-demented subjects with cognitive complaints
  297. (2011). The fate of the 0.5s: predictors of 2-year outcome in mild cognitive impairment. doi
  298. (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. doi
  299. (2000). The nature and staging of attention dysfunction in early (minimal and mild) Alzheimer's disease: relationship to episodic and semantic memory impairment. Neuropsychologia doi
  300. (2012). The Neuropsychological Profile of Alzheimer Disease. Cold Spring Harb Perspect Med doi
  301. (2010). The outcome of elderly patients with cognitive complaints but normal neuropsychological tests.
  302. (2001). The support vector machine under test Neurocomputing 2003; 55: 169-186. Neuropsychological predictors of the outcome in non-demented subjects with cognitive complaints Biomedical Sciences Doctoral Program –
  303. (1936). The use of multiple measurements in taxonomic problems. doi
  304. (2011). The usefulness of the story recall test in patients with mild cognitive impairment and Alzheimer’s disease. doi
  305. (2011). The utility of the spatial span in a clinical geriatric population. doi
  306. (1990). Topographical relationship between beta amyloid and tau protein epitopes in tanglebearing cells in Alzheimer disease. doi
  307. (2011). Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement doi
  308. (2008). Trajectory of mild cognitive impairment onset. doi
  309. (1987). Two types of confabulation. doi
  310. (2012). Unpicking the semantic impairment in Alzheimer's disease: qualitative changes with disease severity. Behav Neurol doi
  311. (1997). Use of a Probabilistic Neural Network to Estimate the Risk of Mortality after Cardiac Surgery. Med Decis Making doi
  312. (2010). Use of SVM methods with surface-based cortical and volumetric subcortical measurements to detect Alzheimer's disease.
  313. (2011). Using biomarkers to improve detection of Alzheimer's disease. Neurodegener Dis Manag doi
  314. (2005). Validating the DemTect with 18-fluoro-2-deoxyglucose positron emission tomography as a sensitive neuropsychological screening test for early alzheimer disease in patients of a memory clinic. Dement Geriatr Cogn Disord doi
  315. (1958). Validity of the Trail Making Test as an indicator of organic brain damage. Percept Mot Skills doi
  316. (2009). Verbal cued recall as a predictor of conversion to Alzheimer's disease in Mild Cognitive Impairment. doi
  317. (2008). Verbal fluency performance in amnestic MCI and older adults with cognitive complaints. Arch Clin Neuropsychol doi
  318. (2007). Verbal learning and memory deficits in Mild Cognitive Impairment. doi
  319. (2012). Verbal learning in Alzheimer's disease and mild cognitive impairment: fine-grained acquisition and short-delay consolidation performance and neural correlates. Neurobiol Aging doi
  320. (1989). Very mild senile dementia of the Alzheimer type. II. Psychometric test performance. doi
  321. (2007). Visual and visuospatial short-term memory in mild cognitive impairment and Alzheimer disease: role of attention. Neuropsychologia doi
  322. (1945). Wechsler Memory Scale (WMS-III; 3th Ed.). doi
  323. (1945). Wechsler memory scale. doi
  324. (2010). WJ; Alzheimer's Disease Neuroimaging Initiative. Comparing predictors of conversion and decline in mild cognitive impairment. Neurology doi
  325. (2011). Working memory in mild cognitive impairment and Alzheimer's disease: contribution of forgetting and predictive value of complex span tasks. Neuropsychology doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.