Radiology leaders outline role-separation models for integrating AI into diagnostic workflows.
Key Details
- 1Editorial published in Radiology advocates clear division of duties between AI and radiologists.
- 2Proposes three models: case allocation, doctor-first sequential, and AI-first sequential.
- 3Case allocation model suggests triaging cases by complexity for AI, radiologists, or both.
- 4Doctor-first model keeps radiologist as initial decision-maker, assisted by AI in reporting and recommendations.
- 5AI-first sequential model involves AI handling initial context, with radiologist interpreting afterward, but has current limitations.
- 6Authors recommend establishing clinical certification pathways for AI systems.
Why It Matters
Clear frameworks and role definition are essential as radiology departments adopt AI tools, mitigating risks like automation bias and optimizing human/AI collaboration. The proposal emphasizes the need for adaptable approaches, fostering safer, more effective diagnostic workflows.

Source
AuntMinnie
Related News

•AI in Healthcare
FDA Seeks Real-World Performance Insights on AI Medical Devices
FDA calls for healthcare worker feedback to enhance monitoring of AI-enabled medical devices in real-world settings.

•Radiology Business
Cigna Expands Nationwide Coverage for CT Imaging AI Tools
Cigna will reimburse for CT-based plaque analysis AI software for millions of members nationwide.

•AI in Healthcare
Joint Commission Issues AI Guidance; Radiology AI Advancements Highlighted
Joint Commission releases AI safety guidance while major advances surface in predictive and radiology AI models.