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

NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...

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 ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

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

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

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...