Prognostic tool could help clinicians identify high-risk cancer patients
Using a versatile problem-solving framework, researchers show how early relapse in lymphoma patients influences their chance for survival.
New AI system could accelerate clinical research
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
Can deep learning transform heart failure prevention?
A deep neural network called CHAIS may soon replace invasive procedures like catheterization as the new gold standard for monitoring heart health.
A fast and flexible approach to help doctors annotate medical scans
“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.
Team including MIT electrical engineer James Fujimoto wins Lasker Award
Professor James Fujimoto and two additional MIT affiliates honored for influential work on optical coherence tomography, which allows rapid detection of retinal disease, among other applications.
AI model can help determine where a patient’s cancer arose
Predictions from the OncoNPC model could enable doctors to choose targeted treatments for difficult-to-treat tumors.