An AI-powered model developed at University of Michigan can read a brain MRI and diagnose a person in seconds, a study suggests.

Severe bleeding is one of the most common and preventable causes of death after traumatic injury, yet currently available tools have poor ability to determine which patients urgently need blood ...

An AI-powered model developed at University of Michigan can read a brain MRI and diagnose a person in seconds, a study suggests. It detected neurological conditions with up to 97.5% accuracy and ...

At Web Summit Qatar, AI-powered biotech startups describe how automation, data, and gene editing are filling labor gaps in ...

BrainIAC, a breakthrough AI foundation model, is able to predict brain age, dementia, time-to-stroke, and brain cancer from brain magnetic resonance imaging (MRI).

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

Background: The heterogeneity in tuberculosis (TB) treatment responses necessitates a precision medicine approach. This study employed machine learning techniques to identify patient subtypes and ...

Objectives Methotrexate (MTX) effectively controls rheumatoid arthritis (RA) but often leads to side effects (SE) such as gastrointestinal (GI) issues, liver toxicity and bone marrow suppression. To ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...