Wrist trackers predict Parkinson’s disease years early
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.
Discover the newest research about AI innovations in 🤖 Machine Learning.
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.

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.

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.

A new study shows video foundation models can grade violent sleep movements, but their tendency to overestimate severity reveals the limits of clinical AI.

A doctor’s self-doubt can degrade the accuracy of medical AI, proving that these systems are highly sensitive to how questions are framed.

A new machine learning model uses basic blood markers to predict how kidney cancer patients respond to immunotherapy.

A new digital twin model shows that one-third of heart failure patients fail cardiac therapy because surgeons are aiming at the wrong target.

An ambitious clinical trial across Australasia is about to test whether machine learning can make split-second decisions to save critically ill patients.