AI-based schizophrenia clinical thinking training simulation system

By constructing an AI-based clinical thinking training simulation system for schizophrenia and utilizing the ICD-10 diagnostic criteria and clinical operating procedures, a systematic and quantitative assessment of clinical thinking training for schizophrenia was achieved. This overcame the limitations of traditional training models and improved the diagnostic capabilities and teaching quality of medical students.

CN121746129APending Publication Date: 2026-03-27THE FIRST AFFILIATED HOSPITAL OF CHONGQING MEDICAL UNIVERSITY
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Patent Information

Application Number
CN202511738932.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-25
Publication Date
2026-03-27

AI Technical Summary

Technical Problem

Traditional clinical thinking training models for schizophrenia lack real interactivity and practicality. The application of existing intelligent robot technology in clinical thinking training for schizophrenia is imperfect, making it difficult to improve medical students' diagnostic abilities. Furthermore, diagnosis is highly subjective and lacks objective evaluation standards.

Method used

We constructed an AI-based clinical thinking training simulation system for schizophrenia. By transforming the ICD-10 diagnostic criteria into a quantitative scoring algorithm and combining it with clinical operation guidelines, we adopted multimodal input, deep learning, and quantitative scoring to build a dual-track assessment system for diagnosis and operation, thereby achieving systematic training and feedback.

Benefits of technology

It has enabled the standardization and quantitative assessment of clinical thinking training, improved the objectivity and accuracy of the assessment, increased training efficiency and teaching quality, reduced teaching costs and risks, and promoted the digitalization and intelligentization of teaching management.

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Abstract

The invention discloses an AI-based schizophrenia clinical thinking training simulation system, which relates to the technical field of artificial intelligence, and is characterized by comprising the steps of constructing a dynamic knowledge base, receiving and preprocessing multi-modal input, performing standardized mapping by extracting keywords, and then performing judgment of a rule layer and a semantic layer. A student question method and a standard answer method in the dynamic knowledge base are sent into a model for response generation, then four-dimensional quantitative scoring and clinical operation multi-dimensional scoring are carried out, error codes and positioning sentences thereof are output, and finally personalized training courses are recommended to students; and hot-updating the dynamic knowledge base continuous optimization model. According to the method, four dimensions of the ICD-10 diagnostic standard are converted into a quantitative scoring algorithm capable of being automatically executed, quantitative assessment of clinical operation specifications is integrated, a diagnosis and operation double-track evaluation system is constructed, the problems that a traditional method is lack of evaluation standards and high in subjectivity are solved, and the evaluation efficiency is improved. Therefore, the evaluation of the clinical thinking ability of the medical students becomes objective, comprehensive and evidence-based.
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