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 ...

Abstract: This research explores the application of machine learning techniques in recommending personalized cancer treatments, comparing supervised learning and reinforcement learning approaches. By ...

Abstract: ADRs, or adverse drug reactions, are a chronic problem in drug development and patient safety, frequently resulting in expensive clinical failures and serious health outcomes. Conventional ...

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).

Background: Implementing machine learning models to identify clinical deterioration on the wards is associated with decreased morbidity and mortality. However, these models have high false positive ...

1 Department of Speech Language Pathology and Audiology, National Taipei University of Nursing and Health Sciences, Taipei City, Taiwan 2 School of Occupational Therapy, College of Medicine, National ...

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 ...

After the flurry of season opening tournaments in December, things settled down last week as most teams were either idle or wrestled limited dual meet schedules. As a result, the individual rankings ...