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Integrating multiple fitting regression and Bayes decision for cancer diagnosis with transcriptomic data from tumor-educated blood platelets.

The Analyst
The application of machine learning in cancer diagnostics has shown great promise and is of importance in clinic settings. Here we consider applying machine learning methods to transcriptomic data derived from tumor-educated platelets (TEPs) from ind...

Computational model for vitamin D deficiency using hair mineral analysis.

Computational biology and chemistry
Vitamin D deficiency is prevalent in the Arabian Gulf region, especially among women. Recent studies show that the vitamin D deficiency is associated with a mineral status of a patient. Therefore, it is important to assess the mineral status of the p...

Classifying patient portal messages using Convolutional Neural Networks.

Journal of biomedical informatics
OBJECTIVE: Patients communicate with healthcare providers via secure messaging in patient portals. As patient portal adoption increases, growing messaging volumes may overwhelm providers. Prior research has demonstrated promise in automating classifi...

Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction.

Psychological science
Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people's self-reported traits and preferences. We used machine learning to test how well such measures pred...

Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting.

Medical physics
PURPOSE: The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid ar...

Rapid Life-Cycle Impact Screening Using Artificial Neural Networks.

Environmental science & technology
The number of chemicals in the market is rapidly increasing, while our understanding of the life-cycle impacts of these chemicals lags considerably. To address this, we developed deep artificial neural network (ANN) models to estimate life-cycle impa...

Finding disagreement pathway signatures and constructing an ensemble model for cancer classification.

Scientific reports
Cancer classification based on molecular level is a relatively routine research procedure with advances in high-throughput molecular profiling techniques. However, the number of genes typically far exceeds the number of the sample size in gene expres...
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Semantic Modeling for Exposomics with Exploratory Evaluation in Clinical Context.

Journal of healthcare engineering
Exposome is a critical dimension in the precision medicine paradigm. Effective representation of exposomics knowledge is instrumental to melding nongenetic factors into data analytics for clinical research. There is still limited work in (1) modeling...
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Elastic network model of learned maintained contacts to predict protein motion.

PloS one
We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein's contact topology. Existing elastic network models assume that the contact topology r...