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 ...

Machine learning can enhance ARF outcome predictions but faces challenges like data quality, system heterogeneity, and clinician acceptance. High ARF mortality and mechanical ventilation risks ...

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 ...

Debate continues over the role of artificial intelligence in treating mental health conditions, but new research shows that machine learning models can help predict whether a person might benefit from ...

Artificial intelligence tools in neuro-oncology demonstrate robust performance in detecting brain metastases and predicting clinical outcomes.

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

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...