Revolutionizing clinical skills training with Generative AI: the Intelligent Inquiry Training System framework

Abstract

Background Practical training bridges theoretical knowledge and clinical skills in medical education but faces challenges such as resource scarcity, complex patient–physician relationship, and limited interactivity in traditional systems. Generative artificial intelligence (LLMs) offers innovative solutions for simulating virtual patients and enhancing communication training. Method An Intelligent Inquiry Training System (IITS) was developed using Baidu’s Wenxin LLM, featuring dynamic case generation, multimodal examination simulation, and emotional feedback modules. Integrated into a blended surgical curriculum, IITS employed pre-class problem-based learning (PBL) and post-class extended training. System efficacy was evaluated via student/instructor questionnaires. Results IITS received software copyright certification and demonstrated cross-platform compatibility. Student feedback highlighted its auxiliary role, prompt responses, and need for improved diagnostic accuracy. Teachers praised its case generation efficiency and recommended AI-powered evaluation. Conclusion IITS enhances clinical reasoning and communication skills through realistic virtual training, reducing teacher workload. Future iterations will integrate AI scoring and simulator mannequins to validate long-term impacts on clinical competency.

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