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

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 ...

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

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...

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 ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Mass General ...

The Santander US Auto business uses FICO® Platform to enhance the use of machine learning capabilities to support credit risk analysis. FICO Platform enables Santander US Auto to build an analytical ...