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 ...
EurekAlert!

AI-optimized decision-making in energy systems: a new approach to integrating machine learning and mathematical programming

Discover how a new AI system is revolutionizing energy management by merging machine learning and mathematical programming. This innovative approach not only boosts prediction accuracy but also ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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, ...