TY - JOUR
T1 - When Traditional Medicine Meets AI
T2 - Critical Considerations for AI-Empowered Clinical Support in Traditional Medicine
AU - Sun, Yuling
AU - Yue, Wenjing
AU - Jin, Xiaofu
AU - Ma, Shuai
AU - Ma, Xiaojuan
AU - Wang, Xiaoling
N1 - Publisher Copyright:
© 2025 ACM.
PY - 2025/10/16
Y1 - 2025/10/16
N2 - 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.
AB - 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.
KW - adoption
KW - artificial intelligence
KW - clinical decision-making
KW - clinician
KW - qualitative
KW - traditional Chinese medicine
KW - traditional medicine
KW - usability
UR - https://www.scopus.com/pages/publications/105019704586
U2 - 10.1145/3757705
DO - 10.1145/3757705
M3 - 文章
AN - SCOPUS:105019704586
SN - 2573-0142
VL - 9
JO - Proceedings of the ACM on Human-Computer Interaction
JF - Proceedings of the ACM on Human-Computer Interaction
IS - 7
M1 - CSCW524
ER -