
Predicting breast cancer six years before diagnosis
A six-year head start on breast cancer sounds like a clinical triumph, but it comes with a massive catch.
Discover the newest research about AI innovations in Research.

A six-year head start on breast cancer sounds like a clinical triumph, but it comes with a massive catch.

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.