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April 25, 20260 citationsOpen Access

AI-Based Simulation Training, Clinical Scenarios, and Digital Assessment in Osce Processes.

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SMSahiyeva MatlubaJBJo'rayev Bekzod

Key Points

  • This research focuses on how AI can improve simulation-based medical training and assessment during clinical examinations.
  • Examined AI-powered simulation platforms that replicate clinical scenarios and enable digital evaluation.
  • Implemented machine learning algorithms for real-time performance scoring and automated feedback mechanisms.
  • Utilized natural language processing for patient interactions within Objective Structured Clinical Examinations (OSCE).
  • AI platforms provided objective and personalized assessments of trainees’ competencies.
  • Adaptive scenario generation improved the relevancy of training experiences for each trainee.
  • Performance scoring with machine learning highlighted specific strengths and areas needing improvement.

Abstract

The integration of artificial intelligence (AI) into simulation-based medical training has transformed traditional approaches to clinical skill development and assessment. This article examines AI-powered simulation platforms that replicate realistic clinical scenarios and enable digital evaluation within Objective Structured Clinical Examinations (OSCE). By employing machine learning algorithms for real-time performance scoring, adaptive scenario generation, natural language processing for patient interaction, and automated feedback mechanisms, AI delivers objective, bias-reduced, and personalized assessment of trainees’ diagnostic, procedural, and communication competencies.

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Cite This Study

Matluba et al. (2026) studied this question.

synapsesocial.com/papers/69ec5ae988ba6daa22dac628https://doi.org/10.5281/zenodo.19712832
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