An AI-Powered Voice-Driven Oral Board Examination Simulator for Radiology Training: A Pilot Feasibility Study.
Authors
Affiliations (2)
Affiliations (2)
- Department of Interventional Radiology, University of Miami, Miller School of Medicine, Miami, Florida.
- Department of Diagnostic Radiology, University of Miami, Miller School of Medicine, Miami, Florida.
Abstract
The American Board of Radiology is transitioning radiology certifying examinations to a virtual oral format in 2028, creating need for scalable preparation tools, as traditional mock orals require significant faculty resources. To develop and evaluate feasibility, usability, and educational value of an AI-powered voice-driven oral board examination simulator. In this IRB-approved single-institution pilot (May 2025-June 2026), we developed RadBoardsAI, a web-based platform with real-time voice interaction (Whisper, GPT-4o, text-to-speech), deterministic examiner constraints, and ABR sample cases. Residents (PGY-2-PGY-5) completed simulated examinations and pre/post surveys. Eight completed baselines; four (50%) post-intervention; 75% had no prior mock oral experience. Baseline confidence (2.57 ± 0.98) and preparedness (2.14 ± 0.90) were low, with moderate stress (3.14 ± 0.90). Post-intervention (n = 4) showed improved confidence (3.50; SMD = + 0.95) and preparedness (3.50; SMD = + 1.51), decreased stress (1.50; SMD = -1.83), and mean SUS 70.0 ± 15.1 (Good). Qualitative feedback identified image labeling and case expansion as priorities. In this pilot feasibility study, RadBoardsAI demonstrates technical feasibility and acceptability among radiology residents, addressing faculty constraints while providing standardized oral board preparation.