A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...
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 ...
Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...
In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.
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