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 ...

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 ...

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

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...

For the first time, researchers have used machine learning – a type of artificial intelligence (AI) – to identify the most important drivers of cancer survival in nearly all the countries in the world ...

The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...