Construction of the digital-to-intelligent transformation in pathological morphology teaching

doi:10.16098/j.issn.0529-1356.2026.06.003

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Acta Anatomica Sinica ›› 2026, Vol. 57 ›› Issue (5) : 536-542. DOI: 10.16098/j.issn.0529-1356.2026.06.003

Digital-Intelligent Anatomy Teaching

Construction of the digital-to-intelligent transformation in pathological morphology teaching

WU Jiang-hua^1,2, WANG Hui^1,2, NI Hua^1,2, TIAN Xin-xia^1,2*, ZHANG Wei-guang³*

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Abstract

Digital pathology technology has overcome the resource limitations inherent in traditional pathological morphology teaching. However, current digital teaching applications are still largely confined to slide image browsing, falling short in supporting self-directed learning, providing interactive functionalities, and establishing effective assessment and feedback mechanisms. Consequently, they fail to meet the competency-focused requirements of modern pathology morphology education. In line with the trend toward intelligent transformation in medical education, in this paper we explored the integration of artificial intelligence (AI) technologies-specifically vision-language pathology foundation models and multimodal knowledge graphs-into the teaching framework and implementation strategies for pathological morphology. We propose a blueprint for constructing an intelligent pathological morphology teaching platform. Its core modules comprise three-dimensional digital specimens, AI-powered slide analysis tools, structured multimodal knowledge graphs, and clinical cases. AI-assisted teaching tests show that AI markedly lowers the difficulty of pathological image recognition, with strong student demand and high promotion willingness. The platform is designed to drive innovation in pathology practical teaching by enhancing digital-intelligent visualization, enabling real-time interactive learning, and facilitating the correlation of theoretical knowledge. This work provides a theoretical framework and practical implementation pathways to support the intelligent transformation of pathological morphology education.

Key words

Basic morphology / Digital pathology / Artificial intelligence / Medical education / Medical student

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WU Jiang-hua, WANG Hui, NI Hua, TIAN Xin-xia, ZHANG Wei-guang. Construction of the digital-to-intelligent transformation in pathological morphology teaching[J]. Acta Anatomica Sinica. 2026, 57(5): 536-542 https://doi.org/10.16098/j.issn.0529-1356.2026.06.003

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