Recently, an increasing number of biological and clinical reports have demonstrated that imbalance of microbial community has the ability to play important roles among several complex diseases concerning human health. Having a good knowledge of disco...
BACKGROUND: Considering the increasing volume of text document information on Internet pages, dealing with such a tremendous amount of knowledge becomes totally complex due to its large size. Text clustering is a common optimization problem used to m...
The journal of prevention of Alzheimer's disease
Jan 1, 2020
The neuropsychological scores and Functional Activities Questionnaire (FAQ) are significant to measure the cognitive and functional domain of the patients affected by the Alzheimer's Disease. Further, there are standardized dataset available today th...
BACKGROUND: In this study, we used a convolutional neural network (CNN) to classify Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal control (NC) subjects based on images of the hippocampus region extracted from magnetic resonanc...
Peptides act as promising anticancer agents due to their ease of synthesis and modifications, enhanced tumor penetration, and less systemic toxicity. However, only limited success has been achieved so far, as experimental design and synthesis of anti...
The chloroplast is a type of subcellular organelle of green plants and eukaryotic algae, which plays an important role in the photosynthesis process. Since the function of a protein correlates with its location, knowing its subchloroplast localizatio...
IMPORTANCE: Detection of cutaneous cancer on the face using deep-learning algorithms has been challenging because various anatomic structures create curves and shades that confuse the algorithm and can potentially lead to false-positive results.
PURPOSE: To develop a deep convolutional neural network (CNN) model to categorize multiphase CT and MRI liver observations using the liver imaging reporting and data system (LI-RADS) (version 2014).
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2020
OBJECTIVE: We aimed to impute uncoded self-harm in administrative claims data of individuals with major mental illness (MMI), characterize self-harm incidence, and identify factors associated with coding bias.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2020
OBJECTIVE: Electronic medical records (EMRs) can support medical research and discovery, but privacy risks limit the sharing of such data on a wide scale. Various approaches have been developed to mitigate risk, including record simulation via genera...
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