Construction of a New Clinical Teaching System for Non-Alcoholic Fatty Liver Disease (NAFLD) based on the Dynamic Training Model Integrating “Guidelines, Clinical Practice, and Scientific Research”

Abstract

With the shift in the definition of disease from non-alcoholic fatty liver disease (NAFLD) to metabolism-associated fatty liver disease (MAFLD), as well as the rapid evolution of pathological classification and therapeutic targets, traditional clinical teaching models face challenges such as outdated guideline updates, disjointed translation of scientific research, and limited skill training. This study proposes a dynamic training model integrating “guidelines, clinical practice, and scientific research.” Through stratified case-based teaching (e.g., FibroScan simulator and metabolic sand table), dynamic guideline analysis (comparing old and new evidence), and the integration of scientific thinking (visualization of CAND1 protein mechanism), a teaching system that integrates theory and practice is constructed. Innovatively developed smart assistant tools (AI decision support system, VR liver biopsy simulator) and a multi-dimensional evaluation system (deviation analysis of diagnosis and treatment pathways, milestone assessment) are used while emphasizing metabolic medicine integration (continuous glucose monitoring and digital therapy) and ethical privacy protection (federated learning framework). This model aims to cultivate students’ evidence-based decision-making skills and scientific research transformation thinking through dynamic knowledge base construction and interdisciplinary collaboration, providing sustainable teaching solutions to cope with the rapid iteration of NAFLD diagnosis and treatment.