AI Medical Compendium Journal:
Experimental biology and medicine (Maywood, N.J.)

Showing 21 to 27 of 27 articles

Evaluation methodology for deep learning imputation models.

Experimental biology and medicine (Maywood, N.J.)
There is growing interest in imputing missing data in tabular datasets using deep learning. Existing deep learning-based imputation models have been commonly evaluated using root mean square error (RMSE) as the predictive accuracy metric. In this art...

Exploring machine learning for audio-based respiratory condition screening: A concise review of databases, methods, and open issues.

Experimental biology and medicine (Maywood, N.J.)
Auscultation plays an important role in the clinic, and the research community has been exploring machine learning (ML) to enable remote and automatic auscultation for respiratory condition screening via sounds. To give the big picture of what is goi...

Imaging and artificial intelligence for progression of age-related macular degeneration.

Experimental biology and medicine (Maywood, N.J.)
Age-related macular degeneration (AMD) is a leading cause of severe vision loss. With our aging population, it may affect 288 million people globally by the year 2040. AMD progresses from an early and intermediate dry form to an advanced one, which m...

Machine learning in optical coherence tomography angiography.

Experimental biology and medicine (Maywood, N.J.)
Optical coherence tomography angiography (OCTA) offers a noninvasive label-free solution for imaging retinal vasculatures at the capillary level resolution. In principle, improved resolution implies a better chance to reveal subtle microvascular dist...

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Experimental biology and medicine (Maywood, N.J.)
Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete. Previous studies suggest that genomic structural variations play an important role in the pathogene...

Trends in application of advancing computational approaches in GPCR ligand discovery.

Experimental biology and medicine (Maywood, N.J.)
G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefo...