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 ...

Investigations suggest V2P may be efficiently applied for the automated identification of causal variants in simulated and actual patient sequencing data across phenotypes.

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...

COVID-19 severity can be predicted by a model with 5 variables: respiratory rate, systolic blood pressure, plasma albumin, LDH, and CRP.