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

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

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 ...

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 ...

To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...