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 ...

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

n this study, 773 untreated breast cancer patients from all over China were collected and followed up for at least 5 years. We obtained clinical data from 773 cases, RNA sequencing data from 752 cases ...

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

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

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

Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...