A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

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 can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

Studying gene expression in a cancer patient's cells can help clinical biologists understand the cancer's origin and predict the success of different treatments. But cells are complex and contain many ...

When Hend Alqaderiwas studying how saliva could predict the risk of diabetes or the severity of a coronavirus infection, she collected a lot of saliva samples-thousands, measuring hundreds of bacteria ...

Discover how AI is transforming nutritional science by turning complex diet and omics data into predictive tools that reshape chronic disease prevention and personalized care.

Apheris's ADMET Network will combine proprietary datasets in a privacy-preserving environment to accelerate AI drug discovery models.

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 ...

Studying gene expression in a cancer patient's cells can help clinical biologists understand the cancer's origin and predict ...

Over the past decade, sports nutrition has quietly become one of the most technologically driven areas of performance support ...

Approximately one in seven adults in the United States has kidney disease, where the organs responsible for filtering waste ...