Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.

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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 new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Given the success of the Digital Medicine and Chronic Neurological Disorders, we are pleased to announce Volume II.Digital medicine is the clinical part of ...

In the study The Shadow and the Self in Digital Twins in Healthcare as an AI Environment, published in AI & Society, researchers explore how digital twins may influence not only medical ...

Metabolite data and AI combine to redefine how we measure aging and predict health spans. Study: Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning ...