The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
News-Medical.Net on MSN

Physical function metrics improve mortality prediction in elderly heart failure patients

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may ...
News-Medical.Net

Machine learning model demonstrates insulin resistance as a risk factor for 12 types of cancer

Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...
University of Birmingham

Machine‑learning framework could transform prediction of drug side effects

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Risk.net

Demand deposit balance prediction models under the interest rate risk in the banking book guidelines: an empirical analysis integrating time-series models and machine learning ...

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

Extreme temperature changes increase number of out-of-hospital cardiac arrests, model finds

In a study published in npj Digital Medicine, a team of researchers led by the University of Michigan developed a machine learning model that identified 17 environmental and social factors that can ...