When Traditional Medicine Meets AI: Critical Considerations for AI-Empowered Clinical Support in Traditional Medicine

Traditional Medicine (TM) is the oldest healthcare form and has been increasingly adopted as the primary or complementary medical therapy in the world. However, TM's practical development remains highly challenging. While artificial intelligence (AI) has become powerful in advancing modern medicine, limited attention has been paid to its potential and usage in TM. This study addresses this gap through a probe-based interview study with 16 TM clinicians, examining their experiences, perceptions, and expectations of AI-empowered clinical support systems. Our findings reveal that despite numerous AI-CDS systems, their practical usage in TM settings was still limited. We identify a series of practical challenges when integrating AI-CDS into TM clinical scenarios, largely due to TM's unique features and the significant data work challenges these features present. We end by critically discussing the potential issues that may arise when integrating AI into practical TM scenarios, and proposing a series of practical recommendations for future studies.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757705
Citations
1
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
2.38
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When Traditional Medicine Meets AI: Critical Considerations for AI-Empowered Clinical Support in Traditional Medicine

Shuai Ma, Xiaojuan Ma, Yuling Sun, Xiaofu Jin et al.
1 citations
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article

When Traditional Medicine Meets AI: Critical Considerations for AI-Empowered Clinical Support in Traditional Medicine

Shuai Ma, Xiaojuan Ma, Yuling Sun, Xiaofu Jin, Wenjing Yue, Xiaoling Wang
article en
1 citations

Abstract

Traditional Medicine (TM) is the oldest healthcare form and has been increasingly adopted as the primary or complementary medical therapy in the world. However, TM's practical development remains highly challenging. While artificial intelligence (AI) has become powerful in advancing modern medicine, limited attention has been paid to its potential and usage in TM. This study addresses this gap through a probe-based interview study with 16 TM clinicians, examining their experiences, perceptions, and expectations of AI-empowered clinical support systems. Our findings reveal that despite numerous AI-CDS systems, their practical usage in TM settings was still limited. We identify a series of practical challenges when integrating AI-CDS into TM clinical scenarios, largely due to TM's unique features and the significant data work challenges these features present. We end by critically discussing the potential issues that may arise when integrating AI into practical TM scenarios, and proposing a series of practical recommendations for future studies.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Hong Kong University of Science and Technology (HK), Fudan University (CN), East China Normal University (CN), Aalto University (FI)
Openalex Percentile: Top 9%
Traditional Chinese Medicine Studies
2.38
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When Traditional Medicine Meets AI: Critical Considerations for AI-Empowered Clinical Support in Traditional Medicine — Shuai Ma, Xiaojuan Ma, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS