Implementing scripted conversations by means of smart assistants

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUGSmart assistants are among the most popular technological devices at home. With a built-in voice-based user interface, they provide access to a broad portfolio of online services and information, and constitute the central element of state-of-the-art home automation systems. This work discusses the challenges addressed and the solutions adopted for the design and implementation of scripted conversations by means of off-the-shelf smart assistants. Scripted conversations play a fundamental role in many application fields, such as call center facilities, retail customer services, rapid prototyping, role-based training or the management of neuropsychiatric disorders. To illustrate this proposal, an actual implementation of the phone version of the Montreal cognitive assessment test as an Amazon's Alexa skill is described as a proof-of-concept.Agencia Estatal de Investigo | Ref. PID2020-115137RB-I00Ministerio de Ciencia, Innovación y Universidades | Ref. FPU19/0198

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Early detection of cognitive impairment through gamification, machine learning tecniques and ict tools

Este trabajo de tese se plantea como la realización de una investigación en el ámbito de la aplicación de las TICs para la detección temprana de posibles riesgos que deriven en un posterior deterioro cognitivo en personas mayores. El principal objetivo es contribuir en la generación de nuevo conocimiento para la detección de forma precoz del Deterioro Cognitivo, es decir, contribuir al desarrollo de nuevos mecanismos de evaluación y diagnóstico del Deterioro Cognitivo o inicio de Demencia, cuya variante más común es la enfermedad del Alzheimer. Consiguientemente se realizarán trabajos desde una perspectiva académica, sistemática y rigurosa orientada a identificar propuestas a nivel global que puedan ser de interés en este ámbito para el Sistema de Salud y de Políticas Sociales. Tras la revisión del estado del arte sobre los actuales mecanismos de evaluación cognitiva, se detectó una posible línea de investigación o “gap research”, debido a la falta de referencias bibliográficas que aporten conocimiento fiable sobre: la evaluación cognitiva de una persona a través de una batería de videojuegos genéricos y técnicas de aprendizaje máquina. Por tanto se pretende abordar el siguiente reto de investigación o hipótesis de trabajo: “¿Es posible crear un artefacto que permita estimar el estado cognitivo de una persona, a partir de su interacción con casual games y utilizando técnicas de aprendizaje máquina?”Este traballo de tese plantéxase coma a realización dunha investigación no eido da aplicación das TIC para a detección temperá de posibles riscos que deriven nun posterior deterioro cognitivo en persoas maiores. O principal obxectivo é contribuír na xeración de novo coñecemento para a detección de forma precoz do Deterioro Cognitivo, é dicir contribuír ao desenvolvemento de novos mecanismos de avaliación e diagnose do Deterioro Cognitivo ou inicio de Demencia, cuxa variante máis común é a enfermidade do Alzheimer. Conseguintemente realizaranse traballos dende unha perspectiva académica, sistemática e rigorosa orientada a identificar propostas a nivel global que poidan ser de interese neste ámbito para o Sistema de Saúde e Políticas Sociais. Trala revisión do estado da arte sobre os actuais mecanismos de avaliación cognitiva, detectouse unha posible liña de investigación ou “gap research”, debido á falta de referencias bibliográficas que aporten coñecemento fiable sobre: a avaliación cognitiva dunha persoa a través dunha batería de videoxogos xenéricos e técnicas de aprendizaxe máquina. Por tanto se pretende abordar o seguinte reto de investigación ou hipótese de traballo: “É posible crear un artefacto que permita estimar o estado cognitivo dunha persoa, a partir da súa interacción con casual games e utilizando técnicas de aprendizaxe máquina?”Este trabajo de tese se plantea como la realización de una investigación en el ámbito de la aplicación de las TICs para la detección temprana de posibles riesgos que deriven en un posterior deterioro cognitivo en personas mayores. El principal objetivo es contribuir en la generación de nuevo conocimiento para la detección de forma precoz del Deterioro Cognitivo, es decir, contribuir al desarrollo de nuevos mecanismos de evaluación y diagnóstico del Deterioro Cognitivo o inicio de Demencia, cuya variante más común es la enfermedad del Alzheimer. Consiguientemente se realizarán trabajos desde una perspectiva académica, sistemática y rigurosa orientada a identificar propuestas a nivel global que puedan ser de interés en este ámbito para el Sistema de Salud y de Políticas Sociales. Tras la revisión del estado del arte sobre los actuales mecanismos de evaluación cognitiva, se detectó una posible línea de investigación o “gap research”, debido a la falta de referencias bibliográficas que aporten conocimiento fiable sobre: la evaluación cognitiva de una persona a través de una batería de videojuegos genéricos y técnicas de aprendizaje máquina. Por tanto se pretende abordar el siguiente reto de investigación o hipótesis de trabajo: “¿Es posible crear un artefacto que permita estimar el estado cognitivo de una persona, a partir de su interacción con casual games y utilizando técnicas de aprendizaje máquina?

Evaluation of the predictive ability and user Aaceptance of Panoramix 2.0, an aI-based e-health tool for the detection of cognitive impairment

The high prevalence of Alzheimer-type dementia and the limitations of traditional neuropsychological tests motivate the introduction of new cognitive assessment methods. We discuss the validation of an all-digital, ecological and non-intrusive e-health application for the early detection of cognitive impairment, based on artificial intelligence for patient classification, and more specifically on machine learning algorithms. To evaluate the discrimination power of this application, a cross-sectional pilot study was carried out involving 30 subjects: 10 health control subjects (mean age: 75.62 years); 14 individuals with mild cognitive impairment (mean age: 81.24 years) and 6 early-stage Alzheimer’s patients (mean age: 80.44 years). The study was carried out in two separate sessions in November 2021 and January 2022. All participants completed the study, and no concerns were raised about the acceptability of the test. Analysis including socio-demographics and game data supports the prediction of participants’ cognitive status using machine learning algorithms. According to the performance metrics computed, best classification results are obtained a Multilayer Perceptron classifier, Support Vector Machines and Random Forest, respectively, with weighted recall values >= 0.9784 ± 0.0265 and F1-score = 0.9764 ± 0.0291. Furthermore, thanks to hyper-parameter optimization, false negative rates were dramatically reduced. Shapley’s additive planning (SHAP) applied according to the eXplicable AI (XAI) method, made it possible to visually and quantitatively evaluate the importance of the different features in the final classification. This is a relevant step ahead towards the use of machine learning and gamification to early detect cognitive impairment. In addition, this tool was designed to support self-administration, which could be a relevant aspect in confinement situations with limited access to health professionals. However, further research is required to identify patterns that may help to predict or estimate future cognitive damage and normative data.Ministerio de Ciencia e Innovación | Ref. PID2020-115137RB-I0

Author Correction: Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education

Author Correction: Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education