The frequency of substance use, early age of initiation, and cannabis-related memory impairments are among the primary ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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, ...

New research published in Machine Learning shows pattern learning is not enough to train AI to tackle games—and abstract representations or hybrid approaches may help. Many AI researchers describe ...

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...