
Joint Commission releases AI safety guidance while major advances surface in predictive and radiology AI models.
Key Details
- 1Joint Commission and Coalition for Health AI (CHAI) released new AI governance and safety guidance for healthcare organizations on Sept. 17.
- 2Guidance covers governance structures, risk reporting, quality monitoring, and user training; feedback is invited for future updates.
- 3The partnership aims to produce governance playbooks and a voluntary AI certification for over 22,000 accredited organizations.
- 4A European team created an AI model, using data from 400,000 UK Biobank patients, that predicts onset of 1,000 diseases up to 10 years in advance—validated on Danish records.
- 5A large US health system deployed a radiology AI tool network-wide; another AI model nearly halved the false positive rate in lung cancer CT screening.
Why It Matters

Source
AI in Healthcare
Related News

Study: Computer Vision Models Best LLMs in Chest CT Breast Abnormality Detection
Computer vision models (CVMs) surpass large language models (LLMs) in accurately labeling incidental breast abnormalities on chest CT scans.

Radiology Maintains Lead in FDA-Cleared AI Algorithms, Cardiology Follows
Radiology remains the top specialty for FDA-cleared AI, with cardiology as a strong second, particularly in cardiovascular imaging.

Deep Learning Models Rival Radiologists for Pancreatic Cancer Detection on CT
Deep-learning models achieved comparable or superior accuracy to experienced radiologists in detecting pancreatic cancer on CT scans, especially for small tumors.