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 ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

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

Using machine learning, an electronic nose can "smell" early signs of ovarian cancer in the blood. The method is precise and, ...

Researchers from Odisha and Saudi Arabia have developed a hybrid AI model achieving 95.49% accuracy in predicting liver disease. This innovative tool, combining deep learning and boosting, promises ...

Adults with congenital heart disease (CHD) have a persistently high risk for cardiac reoperation, according to a new study.

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

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 ...