The study of dental microwear allows the analysis of the microscopic marks that foods leave on the surface of tooth enamel ...

The goals of this study are to describe machine learning techniques employing computer-vision movement algorithms to automatically evaluate infants’ general movements (GMs) in the writhing stage. This ...

The present study evaluates the performance of several statistical, neural, and deep learning methodologies in developing mathematical models for estimating dimensionless parameters associated with ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using machine learning and big data to improve health care and medical research. Both ...

Oxygen depletion in the western Baltic Sea is not uncommon. Oxygen-poor conditions regularly occur in deeper waters, placing stress on marine ecosystems and, in extreme cases, causing fish kills. As ...

A new study reveals how AI analyzes routine retinal eye photos to predict Alzheimer’s lifestyle and biological risk factors ...

Air pollution appears to be a stronger predictor of cardiovascular emergencies than weather conditions alone, a new study that analyzed 23 years of environmental and health data in Taiwan showed. A ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...