The American Journal of Managed Care

Machine Learning May Enable Earlier Detection of CKD Risk Factors

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
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 ...
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 - ...
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 ...
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Machine learning model predicts serious transplant complications months before symptoms appear

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

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 ...