
AI reads rapid tests using synthetic images
Training diagnostic AI no longer requires massive, expensive libraries of real patient photos.
Discover the newest research about AI innovations in Research.

Training diagnostic AI no longer requires massive, expensive libraries of real patient photos.

A decade of silent suffering for endometriosis patients might finally be cut short by a shift toward non-invasive diagnostics.
A new analysis of wearable data shows that tracking how we move during sleep can flag Parkinson’s risk a decade before clinical symptoms appear.

The federal government is loosening its grip on low-risk digital health tools, but developers who mismanage their marketing claims will still face regulatory crackdowns.

A new machine learning model can pinpoint which ankle fracture patients are highly likely to develop surgical infections, but its tendency to miss the majority of at-risk cases makes it a dangerous tool if used as a standalone safety net.

A new regulatory shortcut could quietly solve the worst bottleneck in cancer treatment.

A new machine learning method extracts high-quality heart disease risk data from low-dose scans that doctors usually ignore for calcium scoring.

When algorithms read pathology reports better than the oncologists who ordered them, the bottleneck in cancer care shifts from diagnostic accuracy to human administrative capacity.

A new machine learning approach shows that while AI can easily spot the difference between Parkinson’s and its deadlier lookalikes, pinpointing the exact disease remains incredibly difficult.

When vulnerable teenagers turn to artificial intelligence for mental health advice, they are not finding a cure—they are finding a mirror that tells them what they want to hear.