20,916 research outputs found

    Biomedical Informatics Applications for Precision Management of Neurodegenerative Diseases

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    Modern medicine is in the midst of a revolution driven by “big data,” rapidly advancing computing power, and broader integration of technology into healthcare. Highly detailed and individualized profiles of both health and disease states are now possible, including biomarkers, genomic profiles, cognitive and behavioral phenotypes, high-frequency assessments, and medical imaging. Although these data are incredibly complex, they can potentially be used to understand multi-determinant causal relationships, elucidate modifiable factors, and ultimately customize treatments based on individual parameters. Especially for neurodegenerative diseases, where an effective therapeutic agent has yet to be discovered, there remains a critical need for an interdisciplinary perspective on data and information management due to the number of unanswered questions. Biomedical informatics is a multidisciplinary field that falls at the intersection of information technology, computer and data science, engineering, and healthcare that will be instrumental for uncovering novel insights into neurodegenerative disease research, including both causal relationships and therapeutic targets and maximizing the utility of both clinical and research data. The present study aims to provide a brief overview of biomedical informatics and how clinical data applications such as clinical decision support tools can be developed to derive new knowledge from the wealth of available data to advance clinical care and scientific research of neurodegenerative diseases in the era of precision medicine

    Antiretroviral Non-Adherence is Associated With a Retrieval Profile of Deficits in Verbal Episodic Memory.

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    HIV-associated deficits in verbal episodic memory are commonly associated with antiretroviral non-adherence; however, the specific aspects of memory functioning (e.g., encoding, consolidation, or retrieval) that underlie this established relationship are not well understood. This study evaluated verbal memory profiles of 202 HIV+ participants who underwent a 30-day electronic monitoring of antiretroviral adherence. At the group level, non-adherence was significantly associated with lower scores on immediate and delayed passage recall and word list learning. Retention and recognition of passages and word lists were not related to adherence. Participants were then classified as having either a normal verbal memory profile, a "subcortical" retrieval profile (i.e., impaired free recall with relatively spared recognition), or a "cortical" encoding profile (e.g., cued recall intrusions) based on the Massman et al. ( 1990 ) algorithm for the California Verbal Learning Test. HIV+ participants with a classic retrieval deficit had significantly greater odds of being non-adherent than participants with a normal or encoding profile. These findings suggest that adherence to prescribed antiretroviral regimens may be particularly vulnerable to disruption in HIV+ individuals due to deficits in the complex process of efficiently accessing verbal episodic information with minimal cues. A stronger relationship between non-adherence and passage (vs. word list) recall was also found and may reflect the importance of contextual features in remembering to take medications. Targeted interventions for enhancing and supporting episodic memory retrieval processes may improve antiretroviral adherence and overall health outcomes among persons living with HIV

    Analysis of electroencephalograms in Alzheimer's disease patients with multiscale entropy

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    The aim of this study was to analyse the electroencephalogram (EEG) background activity of Alzheimer’s disease (AD) patients using the Multiscale Entropy (MSE). The MSE is a recently developed method that quantifies the regularity of a signal on different time scales. These time scales are inspected by means of several coarse-grained sequences formed from the analysed signals. We recorded the EEGs from 19 scalp electrodes in 11 AD patients and 11 age-matched controls and estimated the MSE profile for each epoch of the EEG recordings. The shape of the MSE profiles reveals the EEG complexity, and it suggests that the EEG contains information in deeper scales than the smallest one. Moreover, the results showed that the EEG background activity is less complex in AD patients than control subjects. We found significant difference

    Establishing diagnostic criteria: the role of clinical pragmatics

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    The study of pragmatic disorders is of interest to speech-language pathologists who have a professional responsibility to assess and treat communication impairments. However, these disorders, it will be argued in this paper, have a significance beyond the clinical management of clients with communication impairments. Specifically, pragmatic disorders can now make a contribution to the diagnosis of a range of clinical conditions in which communication is adversely affected. These conditions include attention deficit hyperactivity disorder (ADHD), the autistic spectrum disorders, schizophrenia and the dementias. Pragmatic disorders are already among the criteria used to diagnose some of these conditions (e.g. ADHD), although they are not described in these terms. In other conditions (e.g. the dementias), pragmatic disorders have potential diagnostic value in the absence of reliable biomarkers markers of these conditions and similar initial presenting symptoms. Using clinical data, and the findings of empirical studies, the case is made for the inclusion and/or greater integration of pragmatic disorders in the formal classificatory systems that are used to diagnose a range of disorders. A previously unrecognised role for pragmatic impairments in the nosology and diagnosis of clinical disorders is thereby established
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