The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...
Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...
ICU patients’ needs can change rapidly. The AI studies each patient to make personalized nutrition predictions. In A Nutshell ...
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AI trained on sleep data predicts future disease and mortality years in advance
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
A team led by Guoyin Yin at Wuhan University and the Shanghai Artificial Intelligence Laboratory recently proposed a modular machine learning ...
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