Discover the newest research about AI innovations in Research.
Standard security tools fail to stop medical AI from leaking patient data because the most dangerous clinical hacks look like completely normal requests.
A new computational pathology model exposes the limits of human sight in oncology, diagnosing complex brain tumors in minutes rather than weeks.
A new study reveals that basic physiological math outpaces complex large language models at predicting patient crash times.
A new active learning model proves that medical AI does not need massive, expensive datasets to outperform human-labeled benchmarks.
Hospital IT departments eyeing generative AI for medication safety may want to pause, as a new benchmark reveals that some top-tier models behave like hyper-anxious assistants that flag almost everything as a hazard.
A new computational model uses a single brain scan to predict adolescent anxiety and depression before symptoms fully emerge.
The federal push to let autonomous AI diagnose patients and prescribe drugs is setting up a dangerous collision between political speed and medical safety.
A new machine learning model uses dual ultrasound measurements to identify severe liver damage, offering a way to bypass painful and risky biopsies.
Regulators just crossed a digital rubicon by accepting AI-generated pathology data to evaluate metabolic liver disease treatments.
Standard genetic tests miss the complex networks of DNA variants that cause multiple diseases in the same family, but a new topological AI approach could change how we find them.
