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 ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...
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 ...
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. Researchers ...
12don MSN
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 ...
MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
Explore how machine learning in insurance enhances risk assessment, fraud detection, and personalization. ✓ Subscribe for ...
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