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 ...

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

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more personalized vaccines, including vaccines for cancer. They described the tool in ...

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 ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...

More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care. Today, over 30 ...

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

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, ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...