
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

•AuntMinnie
AI Model Uses Ultrasound to Assess Fetal Lung Maturity
Researchers demonstrated an AI model's strong accuracy in measuring fetal lung maturity from ultrasound images.

•AuntMinnie
AI Model Predicts Dosimetry for Lu-177 PSMA Therapy Using PET/CT
A machine learning PET/CT model shows promise for predicting radiation dose prior to Lu-177 PSMA therapy in prostate cancer patients.

•AuntMinnie
AI Advances in Ultrasound Highlighted at AIUM 2026 Keynote
AI is increasingly enhancing ultrasound imaging, clinical workflows, and education, though challenges in trust and implementation remain.