An examination of fast similarity search trees with gating

The emergence of complex data objects that must be indexed and queried in databases has created a need for access methods that are both generic and efficient. Traditional search algorithms that only check specified fields and keys are no longer effective. Tree-structured indexing techniques based on metric spaces are widely used to solve this problem. Unfortunately, these data structures can be slow as the computational complexity of computing the distance between two points in a metric space can be high. This thesis will explore data structures for the evaluation of range queries in general metric spaces. The performance limitations of metric spaces will be analyzed and opportunities for improvement will be discussed. It will culminate with the introduction of the Fast Similarity Search Tree as a viable alternative to existing methodologies

development of measures of polyneuropathy impairment in hattr amyloidosis from nis to mnis 7

Abstract Hereditary transthyretin-mediated amyloidosis (hATTR amyloidosis) is a rare, life-threatening disease, caused by point mutations in the transthyretin gene. It is a heterogeneous, multisystem disease with rapidly progressing polyneuropathy (including sensory, motor, and autonomic impairments) and cardiac dysfunction. Measures used to assess polyneuropathy in other diseases have been tested as endpoints in hATTR amyloidosis clinical trials (i.e. Neuropathy Impairment Score [NIS], NIS-lower limb, and NIS + 7), yet the unique nature of the polyneuropathy in this disease has necessitated modifications to these scales. In particular, the heterogeneous impairment and the aggressive disease course have been key drivers in developing scales that better capture the disease burden and progression of polyneuropathy in hATTR amyloidosis. The modified NIS + 7 (mNIS + 7) scale was specifically designed to assess polyneuropathy impairment in patients with hATTR amyloidosis, and has been the primary endpoint in two recent, phase III studies in this disease. The mNIS + 7 uses highly standardized, quantitative, and referenced assessments to quantify decreased muscle weakness, muscle stretch reflexes, sensory loss, and autonomic impairment. Physicians using this scale in clinical trials should be specifically trained and monitored to minimize variability. This article discusses the different scales that have been/are being used to assess polyneuropathy in patients with hATTR amyloidosis, their correlation with other disease assessments, and reflects on how and why scales have evolved to the latest iteration of mNIS + 7

Automated extraction of potential migraine biomarkers using a semantic graph

Problem Biomedical literature and databases contain important clues for the identification of potential disease biomarkers. However, searching these enormous knowledge reservoirs and integrating findings across heterogeneous sources is costly and difficult. Here we demonstrate how semantically integrated knowledge, extracted from biomedical literature and structured databases, can be used to automatically identify potential migraine biomarkers. Method We used a knowledge graph containing more than 3.5 million biomedical concepts and 68.4 million relationships. Biochemical compound concepts were filtered and ranked by their potential as biomarkers based on their connections to a subgraph of migraine-related concepts. The ranked results were evaluated against the results of a systematic literature review that was performed manually by migraine researchers. Weight points were assigned to these reference compounds to indicate their relative importance. Results Ranked results automatically generated by the knowledge graph were highly consistent with results from the manual literature review. Out of 222 reference compounds, 163 (73%) ranked in the top 2000, with 547 out of the 644 (85%) weight points assigned to the reference compounds. For reference compounds that were not in the top of the list, an extensive error analysis has been performed. When evaluating the overall performance, we obtained a ROC-AUC of 0.974. Discussion Semantic knowledge graphs composed of information integrated from multiple and varying sources can assist researchers in identifying potential disease biomarkers

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets

Benefits and problems of electronic information exchange as perceived by health care professionals: an interview study

<p>Abstract</p> <p>Background</p> <p>Various countries are currently implementing a national electronic patient record (n-EPR). Despite the assumed positive effects of n-EPRs, their overall adoption remains low and meets resistance from health care providers. This study aims to increase our understanding of health care providers' attitude towards the n-EPR, by investigating their perceptions of the benefits and problems of electronic information exchange in health care and the n-EPR in particular.</p> <p>Methods</p> <p>The study was conducted in three Dutch health care settings: acute care, diabetes care, and ambulatory mental health care. Two health care organisations were included per setting. Between January and June 2010, interviews were conducted with 17 stakeholders working in these organisations. Relevant themes were deduced by means of thematic qualitative analysis.</p> <p>Results</p> <p>Health care providers perceived electronic information exchange to promote the efficiency and quality of care. The problems they perceived in electronic information exchange mainly concerned the confidentiality and safety of information exchange and the reliability and quality of patient data. Many problems perceived by health care providers did not specifically apply to the n-EPR, but to electronic information exchange in general.</p> <p>Conclusions</p> <p>The implementation of the Dutch n-EPR has mainly followed a top-down approach, thereby neglecting the fact that the perceptions and preferences of its users (health care providers) need to be addressed in order to achieve successful implementation. The results of this study provide valuable suggestions about how to promote health care providers' willingness to adopt electronic information exchange, which can be useful for other countries currently implementing an n-EPR. Apart from providing information about the benefits and usefulness of electronic information exchange, efforts should be focused on minimising the problems as perceived by health care providers. The safety and confidentiality of electronic information exchange can be improved by developing tools to evaluate the legitimacy of access to electronic records, by increasing health care providers' awareness of the need to be careful when using patient data, and by measures to limit access to sensitive patient data. Improving health care providers' recording behaviour is important to improve the reliability and quality of electronically exchanged patient data.</p

Piecing it together: atrophy profiles of hippocampal subfields relate to cognitive impairment along the Alzheimer’s disease spectrum

IntroductionPeople with Alzheimer’s disease (AD) experience more rapid declines in their ability to form hippocampal-dependent memories than cognitively normal healthy adults. Degeneration of the whole hippocampal formation has previously been found to covary with declines in learning and memory, but the associations between subfield-specific hippocampal neurodegeneration and cognitive impairments are not well characterized in AD. To improve prognostic procedures, it is critical to establish in which hippocampal subfields atrophy relates to domain-specific cognitive declines among people along the AD spectrum. In this study, we examine high-resolution structural magnetic resonance imaging (MRI) of the medial temporal lobe and extensive neuropsychological data from 29 amyloid-positive people on the AD spectrum and 17 demographically-matched amyloid-negative healthy controls.MethodsParticipants completed a battery of neuropsychological exams including select tests of immediate recollection, delayed recollection, and general cognitive status (i.e., performance on the Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). Hippocampal subfield volumes (CA1, CA2, CA3, dentate gyrus, and subiculum) were measured using a dedicated MRI slab sequence targeting the medial temporal lobe and used to compute distance metrics to quantify AD spectrum-specific atrophic patterns and their impact on cognitive outcomes.ResultsOur results replicate prior studies showing that CA1, dentate gyrus, and subiculum hippocampal subfield volumes were significantly reduced in AD spectrum participants compared to amyloid-negative controls, whereas CA2 and CA3 did not exhibit such patterns of atrophy. Moreover, degeneration of the subiculum along the AD spectrum was linked to a significant decline in general cognitive status measured by the MMSE, while degeneration scores of the CA1 and dentate gyrus were more widely associated with declines on the MMSE and tests of learning and memory.DiscussionThese findings provide evidence that subfield-specific patterns of hippocampal degeneration, in combination with cognitive assessments, may constitute a sensitive prognostic approach and could be used to better track disease trajectories among individuals on the AD spectrum