
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
The Joint Commission-CHAI guidelines provide a concrete framework for AI governance and risk management, critical as radiology and imaging AI become more integrated into clinical workflows. Predictive and imaging AI model advances reinforce the transformative impact of AI on preventive care and radiology practice.

Source
AI in Healthcare
Related News

•HealthExec
New Report Highlights Clinical AI Performance, Sustainability, and Adoption Challenges
A multi-institutional review details key challenges, progress, and sustainability concerns in deploying clinical AI in real-world healthcare settings.

•Cardiovascular Business
FDA Clears AI Platform for Comprehensive Cardiac Risk Assessment on CT
HeartLung Corporation's AI-CVD receives FDA clearance for opportunistic multi-condition screening on routine chest CT scans.

•AuntMinnie
LLM Boosts Terminology Expansion in Radiology Reports Over RadLex
A large language model (LLM) significantly outperforms RadLex in expanding terms for radiology report language standardization.