Discover the newest research about AI innovations in 🤖 Machine Learning.
Static bone density scans miss how a patient’s body changes over time, but a new deep learning model proves that tracking those physical trajectories can prevent missed fracture risks.
A new UK regulatory initiative is putting AI to the test to solve the pharmaceutical industry’s most expensive problem: high failure rates.
Doctors write down clues about their patients’ loneliness, but those warnings usually sit buried in unstructured text where no one can find them.
Training diagnostic AI no longer requires massive, expensive libraries of real patient photos.
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.
