AIMC Topic:
Cluster Analysis
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Near Full-length Genomic Sequencing and Molecular Analysis of HIV-Infected Individuals in a Network-based Intervention (TRIP) in Athens, Greece: Evidence that Transmissions Occur More Frequently from those with High HIV-RNA.
Current HIV research
Jan 1, 2018
BACKGROUND: TRIP (Transmission Reduction Intervention Project) was a network-based, contact tracing approach to locate and link to care, mostly people who inject drugs (PWID) with recent HIV infection.
Machine-Learning Prediction of Drug-Induced Cardiac Arrhythmia: Analysis of Gene Expression and Clustering.
Critical reviews in biomedical engineering
Jan 1, 2018
A marked delay in the electrical repolarization of heart ventricles is characterized by prolongation of the Q-T wave (QT) interval on a surface electrocardiogram. Such a delay can lead to potentially life-threatening cardiac arrhythmia (torsades de p...
Drug Design
Gene Expression Profiling
Mice
Rats
Reproducibility of Results
Sensitivity and Specificity
Animals
Male
Heart
Drug Evaluation, Preclinical
Heart Ventricles
Arrhythmias, Cardiac
Electrocardiography
Support Vector Machine
Cluster Analysis
Signal Processing, Computer-Assisted
Humans
Machine Learning
Female
False Positive Reactions
Torsades de Pointes
MAP Kinase Signaling System
Gene Expression Regulation
Clinical Trials as Topic
Big-Data Analysis, Cluster Analysis, and Machine-Learning Approaches.
Advances in experimental medicine and biology
Jan 1, 2018
Medicine will experience many changes in the coming years because the so-called "medicine of the future" will be increasingly proactive, featuring four basic elements: predictive, personalized, preventive, and participatory. Drivers for these changes...
Impact of Imputing Missing Data in Bayesian Network Structure Learning for Obstructive Sleep Apnea Diagnosis.
Studies in health technology and informatics
Jan 1, 2018
Numerous diagnostic decisions are made every day by healthcare professionals. Bayesian networks can provide a useful aid to the process, but learning their structure from data generally requires the absence of missing data, a common problem in medica...
Machine learning and deep analytics for biocomputing: call for better explainability.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
The goals of this workshop are to discuss challenges in explainability of current Machine Leaning and Deep Analytics (MLDA) used in biocomputing and to start the discussion on ways to improve it. We define explainability in MLDA as easy to use inform...
Intravoxel Incoherent Motion: Model-Free Determination of Tissue Type in Abdominal Organs Using Machine Learning.
Investigative radiology
Dec 1, 2017
PURPOSE: For diffusion data sets including low and high b-values, the intravoxel incoherent motion model is commonly applied to characterize tissue. The aim of the present study was to show that machine learning allows a model-free approach to determ...
Identifying Distinct Subgroups of ICU Patients: A Machine Learning Approach.
Critical care medicine
Oct 1, 2017
OBJECTIVES: Identifying subgroups of ICU patients with similar clinical needs and trajectories may provide a framework for more efficient ICU care through the design of care platforms tailored around patients' shared needs. However, objective methods...
Using neural networks for reducing the dimensions of single-cell RNA-Seq data.
Nucleic acids research
Sep 29, 2017
While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges. These include ...
Deep learning-based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms.
Bioinformatics (Oxford, England)
Jul 15, 2017
MOTIVATION: Cellular Electron CryoTomography (CECT) enables 3D visualization of cellular organization at near-native state and in sub-molecular resolution, making it a powerful tool for analyzing structures of macromolecular complexes and their spati...
Automated cell type discovery and classification through knowledge transfer.
Bioinformatics (Oxford, England)
Jun 1, 2017
MOTIVATION: Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and h...
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