Researchers have trained an artificial intelligence model to extract warning signs of advanced heart failure from routine echocardiogram videos, flagging disease progression years before conventional ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

Researchers have built a machine-learning model that can distinguish between Alzheimer’s disease, dementia with Lewy bodies, ...

To build a self-supervised magnetic resonance imaging (MRI) foundation model from routine clinical scans and to test whether it can support key glioma-related applications, including post-therapy ...

Scientists at Sanford Burnham Prebys Medical Discovery Institute have developed a new computational tool, TLPath, that can infer changes occurring at the ends of chromosomes—the telomeres—by detecting ...

Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.

Deciding whether to administer chemotherapy after surgery is one of the most challenging questions in early-stage breast cancer care. While chemotherapy can reduce the risk of recurrence, most ...

Relying on one giant AI model for everything is a trap; it’s too expensive and slow for simple tasks and too risky for the ...