Nature

Machine learning for quantitative LIBS analysis of aluminum alloys: a comparison of random forest, gradient boosting, and extremely randomized trees

Laser-induced breakdown spectroscopy (LIBS) is a versatile technique for characterizing materials and analyzing elements, but it is limited in its quantitative accuracy due to nonlinear effects. This ...
Nature

Cardiovascular risk prediction via ensemble machine learning and oversampling methods

Cardiovascular disease (CVD) remains one of the leading causes of mortality worldwide. The cardiovascular system comprises the heart and its blood vessels. CVD encompasses four major conditions: ...
TechRepublic

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft

Find out how this structured machine learning roadmap called I-Con could lead to breakthroughs in AI. A new “periodic table for machine learning” is reshaping how researchers explore AI, unlocking ...
EurekAlert!

Machine learning outperforms traditional statistical methods in addressing missing data in electronic health records

Researchers from the National Institute of Health Data Science at Peking University and the Department of Clinical Epidemiology and Biostatistics at Peking University People's Hospital have conducted ...
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 ...