From guesswork to guidance: How machine learning speeds dopant design for water-splitting photocatalysts

MLIP calculations successfully identify suitable dopants for a novel photocatalytic material, report researchers from the ...

Machine learning models identify key predictors of driving under the influence of alcohol or cannabis

The frequency of substance use, early age of initiation, and cannabis-related memory impairments are among the primary factors contributing to driving under the influence, according to a new analysis ...
Frontiers

Soft Computing and Machine Learning Applications for Healthcare Systems

Soft Computing (SC) is an Artificial Intelligence (AI) approach that is more effective at solving real-life problems than traditional computing models. Soft Computing models are tolerant of partial ...

Mapping 3D-super-enhancers with machine learning to pinpoint regulators of cell identity

Scientists usually study the molecular machinery that controls gene expression from the perspective of a linear, two-dimensional genome—even though DNA and its bound proteins function in three ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

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 ...

AI model improves flood forecasting with higher accuracy than current methods

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...
Science Daily

Exploring factors affecting workers' acquisition of exercise habits using machine learning approaches

Researchers analyzed data from middle-aged workers who had received Specific Health Guidance -- a revolutionary system implemented by the Japanese Ministry of Health, Labor, and Welfare to improve ...
Morningstar

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
Chromatography Online

AI/ML in Practice: Boudewijn Hollebrands on Deep Learning Models to Predict Food Peptide Retention Times

LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...