This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...
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 ...
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 ...
Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...
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 ...
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 ...
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 ...
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, ...
When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...
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