aceROECSG report: Real-world implementation patterns and perceptions of artificial intelligence in radiation oncology
Purpose: While international surveys have examined radiation oncology professionals' attitudes toward artificial intelligence (AI) and documented generally low early utilization, actual implementation patterns and the depth of integration among engaged practitioners remain unclear. This multi-institutional survey aims to characterize current AI implementation, identify critical barriers to optimization, and evaluate the psychological factors driving clinical trust. Methods and materials: A de-identified survey c…
AI implementation in radiation oncology is concentrated in auto-contouring, with limited use in diagnosis and planning, while understanding is middling and transparency and validation barriers block deeper adoption.
The study used a convenience sample of 80 respondents, and the authors note that self-selection likely inflates the reported AI use rate relative to the broader field.
Evidence
- Peer-reviewedJournal of Applied Clinical Medical Physics2026-11-01
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Truvace Impact Record TRV-2026-2202, v1: “ROECSG report: Real-world implementation patterns and perceptions of artificial intelligence in radiation oncology.” Truvace, 2026-10-23. /record/TRV-2026-2202 (accessed at citation time). sha256 b07186706b06afca…
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