Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...
Advancing Superior Accuracy in Early Lung Cancer Detection Using Selective Metabolic Pathways and Data Enrichment for ...
IEEE Spectrum on MSN
Machine learning system monitors patient pain during surgery
To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...
For the first time, researchers have used machine learning—a type of artificial intelligence (AI)—to identify the most ...
UT biochemistry major Milit Patel collaborated with researchers at Memorial Sloan Kettering Cancer Center on research published in a top cancer journal.
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 ...
Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...
Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
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