Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
Scholars analyze how the use of machine learning could reshape EPA drinking water standards.
A new study published in the International Journal of General Medicine showed that physicians may reliably estimate the ...
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
Philstar.com on MSN
Study shows reliable model to predict licensure exam outcome
A study conducted by experts from the University of the Philippines-Diliman showed that logistic regression is a reliable ...
A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing ...
3don MSN
A urine-based biological aging clock: Machine learning and microRNA offer accurate prediction
Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...
The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...
News-Medical.Net on MSN
Blood metabolite profiling outperforms BMI in predicting pregnancy complications
This study shows that a blood-based metabolomic signature linked to maternal BMI predicts gestational diabetes and ...
A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing high-volume liposuction, reports a study in the January issue of Plastic and ...
Doctors treating ICU patients on ventilators face a constant challenge regarding nutrition. Now, an AI system can help.
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