A Knowledge Graph–Driven Hypergeometric Efficacy Prediction Model (HEPM) for Classical Traditional Chinese Herbal Formulas

HEPM provides a statistically grounded and interpretable framework for modeling efficacy formation in TCM herbal formulas. The method offers a replicable approach for efficacy prediction and supports the development of knowledge-driven intelligent TCM analysis and clinical decision-support applications.

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Publication Details

Journal
Methods of Information in Medicine
Published
2026-03-27
DOI
https://doi.org/10.1055/a-2841-4549
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

A Knowledge Graph–Driven Hypergeometric Efficacy Prediction Model (HEPM) for Classical Traditional Chinese Herbal Formulas

Fangzhou Liu, Yi Qin, Hongming Ma, Yihao Li et al.
Methods of Information in Medicine
Traditional Chinese Medicine Studies
article

A Knowledge Graph–Driven Hypergeometric Efficacy Prediction Model (HEPM) for Classical Traditional Chinese Herbal Formulas

Fangzhou Liu, Yi Qin, Hongming Ma, Yihao Li, Yu Du, Yang Yang, Yuanbai Li, Meng Li
article en

Abstract

HEPM provides a statistically grounded and interpretable framework for modeling efficacy formation in TCM herbal formulas. The method offers a replicable approach for efficacy prediction and supports the development of knowledge-driven intelligent TCM analysis and clinical decision-support applications.

Methods of Information in Medicine
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Traditional Chinese Medicine Studies
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