Discover the newest research about AI innovations in 🖼️ Computer Vision.
A new clinical trial shows that AI can guide untrained operators to perform deep vein thrombosis scans, but the real value lies in filtering the patient queue rather than replacing human specialists.
A new study shows that even advanced vision models struggle to predict preterm birth when tested on new hospital equipment.
Point-of-care cardiac assessment is moving from subjective clinical guesswork to automated, real-time quantification.
Hospital buyers assume all top-tier radiology AI performs the same, but new head-to-head data reveals critical trade-offs that could compromise patient care if ignored.
Automating the routine mechanics of ultrasound exams is no longer a luxury; it is becoming a survival strategy for short-staffed clinics.
A new multimodal AI model helps solve the agonizing clinical dilemma of whether breast cancer survivors should endure five extra years of hormone therapy.
A new deep learning model bypasses expensive brain scans by reading signs of dementia and stroke directly from the back of the eye.
Training diagnostic AI no longer requires massive, expensive libraries of real patient photos.
A new machine learning method extracts high-quality heart disease risk data from low-dose scans that doctors usually ignore for calcium scoring.
A new study shows video foundation models can grade violent sleep movements, but their tendency to overestimate severity reveals the limits of clinical AI.
