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 ...
Nature

Machine Learning Approaches for Thyroid Disease Diagnosis and Prediction

Recent advances in machine learning have significantly enhanced the diagnosis and prediction of thyroid diseases. By integrating diverse algorithms including ensemble methods, neural networks, and ...

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 ...
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 ...
Science Daily

'Periodic table of machine learning' could fuel AI discovery

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

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 ...
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 ...
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 ...
ascopubs.org

Machine learning–driven approaches for predicting T-cell–mediated immunity and beyond.

Effect of KROS 101, a small molecule GITR ligand agonist, on T effector cells, T reg cells and intratumoral CD8 T cell cytotoxicity. Phase 1 study of DK210 (EGFR), a tumor-targeted IL2 x IL10 dual ...