A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

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 ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

ICU patients’ needs can change rapidly. The AI studies each patient to make personalized nutrition predictions. In A Nutshell ...

Accurately predicting complex agronomic traits remains a major bottleneck in crop breeding. This study demonstrates how ...

For the first time, researchers have used machine learning—a type of artificial intelligence (AI)—to identify the most ...