Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Machine learning model improves transplant risk assessment for patients with myelofibrosis, helping clinicians make informed decisions, as per an expert. A new machine learning model has significantly ...

My company, Kickfurther, has carved out a niche by connecting businesses in need of funding for their retail inventory with buyers of that inventory. A key component of this business model is the ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

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 ...

Researchers used advanced machine learning to increase the accuracy of a national cardiovascular risk calculator while preserving its interpretability and original risk associations. Risk calculators ...

Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...

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 ...

Heart specialists at Mayo Clinic today presented new research at the 2026 Society of Thoracic Surgeons Annual Meeting that ...