An AI-Powered Platform for Radiology Education

[Submitted on 16 Sep 2025]

View a PDF file from the paper entitled Radgame: A platform that works with works to teach radiology, by Muhammad Bhaaron and 31 other authors

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a summary:We offer Radgame, the GamFied platform that works from artificial intelligence to teach radiology that targets two basic skills: localizing results and generating reports. Training on traditional radiology depends on negative exposure to active situations or practice with actual time inputs of supervisory radiologists, and reduce immediate and developed comments opportunities. Radgame deals with this gap by combining Gamification, widely general data groups and automatic comments driven by artificial intelligence that provide clear guidelines for human learners. In the translation of Radgame, players draw specific funds on distortions, which are automatically compared to explanations drawn by the radiologist from general data collections, and visual interpretations are created by vision language models for the missed results of the user. In the RadGame report, players are creating results in view of X -rays on the chest, patient age and signal, and they receive the organization of the AI ​​organization based on the scales of the radiology report generation, highlighting errors and negligence compared to the written truth of the radiologist from public data groups, which results in a final degree and pattern pattern. In a future evaluation, participants who use Radgame achieved a 68 % improvement in the accuracy of localization compared to 17 % with traditional negative methods and improving 31 % in the accuracy of the reports writing compared to 4 % with traditional methods after seeing the same cases. Radgame highlights the gamification capabilities that are driven by artificial intelligence to provide remedial and rich training and reinforcing medical intelligence resources in education.