Evidence map›Paper›PMID 42293429›Full record

ArticleIntegrative medicine research2026

Design and methodology of the AI-empowered Clinical Evidence for Integrated Chinese-Western Medicine (ACE-iMed) platform.

Hui Liu, Ke Xu, Jie Zhang, Shouyuan Wu, Yishan Qin, Yanfang Ma, Xuan Yu, Huayu Zhang, Haodong Li, Meihua Wu and 17 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Integrative medicine research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

27 authors.

Hui LiuResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Ke XuVincent V.C. Woo Chinese Medicine Clinical Research Institute, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China.
Jie ZhangResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Shouyuan WuEvidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Yishan QinResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Yanfang MaVincent V.C. Woo Chinese Medicine Clinical Research Institute, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China.
Xuan YuChinese EQUATOR Centre, Hong Kong Baptist University, Hong Kong SAR, China.
Huayu ZhangSchool of Public Health, Lanzhou University, Lanzhou, China.
Haodong LiSchool of Public Health, Lanzhou University, Lanzhou, China.
Meihua WuSchool of Public Health, Lanzhou University, Lanzhou, China.
Zijing WangSchool of Public Health, Lanzhou University, Lanzhou, China.
Xufei LuoResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Bingyi WangResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Yuanyuan YaoResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Yandong FengResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Luyuan SunResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Mengyue DongInstitute of Integrated Chinese and Western Medicine, School of Basic Medicine Sciences, Lanzhou University, Lanzhou, China.
Yingjie HongInstitute of Integrated Chinese and Western Medicine, School of Basic Medicine Sciences, Lanzhou University, Lanzhou, China.
Jiayi LiuSchool of Public Health, Lanzhou University, Lanzhou, China.
Rui YangSchool of Basic Medicine, Gansu University of Chinese Medicine, Lanzhou, China.
Yiming HuCollege of Traditional Chinese Medicine, Gansu University of Chinese Medicine, Lanzhou, China.
Honghao LaiSchool of Public Health, Lanzhou University, Lanzhou, China.
Qi ZhouResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Xuefeng LiInstitute of Integrated Chinese and Western Medicine, School of Basic Medicine Sciences, Lanzhou University, Lanzhou, China.
Long GeSchool of Public Health, Lanzhou University, Lanzhou, China.
Yaolong ChenResearch Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences (2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Zhaoxiang BianVincent V.C. Woo Chinese Medicine Clinical Research Institute, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Integrated Chinese-Western medicine (ICWM) is a distinctive medical system that plays an important role in healthcare and has received increasing attention in recent years. To facilitate the dissemination of evidence in ICWM, we developed an Artificial Intelligence (AI)-empowered Clinical Evidence for Integrated Chinese-Western Medicine (ACE-iMed) platform. Methods: A multidisciplinary working group was established, including individuals with professional backgrounds in evidence-based medicine methodology, Chinese medicine (CM), Western medicine (WM), and ICWM clinical practice and research, and computer science. Through multiple rounds of discussions, the working group defined the framework and methodology of the platform, and then applied the platform to summarize evidence for eight diseases. Results: The ACE-iMed platform (website: www.aceimed.org) contains two interfaces. The first enables the developers to store and screen the literature, perform methodological quality assessments, and generate evidence summaries. The AI-empowered workflows showed good consistency and stability across multiple stages, including literature screening and assessment of risk of bias/methodological quality, and effectively support summarizing evidence for eight diseases. The second interface, intended for end users, provides synchronized access to the included literature and the generated summaries, enabling quick access to clinical question-oriented evidence resources. Conclusion: This study introduces an AI-empowered, clinical question-oriented ICWM evidence platform. Application across eight diseases demonstrated the platform's feasibility and practical utility. The platform not only supports the developers in summarizing evidence but also provides end users with a potential pathway to access evidence and its summaries.

Indexed as

ACE-iMed platformArtificial intelligenceChinese medicineEvidenceIntegrated Chinese-Western medicineLarge language model

Identifiers

PMID42293429
PMCPMC13253118

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.