Evidence map›Paper›PMID 35692572›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

Establishing a Regulatory Science System for Supervising the Application of Artificial Intelligence for Traditional Chinese Medicine: A Methodological Framework.

Ying He, Qian Wen, Ying Wang, Juan Li, Ning Li, Rongjiang Jin, Nian Li, Yonggang Zhang

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 32% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
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

8 authors at 3 institutions in 1 country.

Ying HeDepartment of Integrated Traditional and Western Medicine, West China Hospital, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0002-3999-2655
Qian WenDepartment of Integrated Traditional and Western Medicine, West China Hospital, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0002-4035-2903
Ying WangDepartment of Medical Administration, West China Hospital, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0001-7535-088X
Juan LiSchool of Health Preservation and Rehabilitation, Traditional Chinese Medicine of Chengdu University, Chengdu, Sichuan, China.
Ning LiDepartment of Integrated Traditional and Western Medicine, West China Hospital, Sichuan University, Chengdu, China.
Rongjiang JinSchool of Health Preservation and Rehabilitation, Traditional Chinese Medicine of Chengdu University, Chengdu, Sichuan, China.
Nian LiDepartment of Medical Administration, West China Hospital, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0003-3253-2565
Yonggang ZhangDepartment of Periodical Press, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID https://orcid.org/0000-0002-5251-3815
Sichuan University · CNChengdu University of Traditional Chinese Medicine · CNWest China Medical Center of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we reported a methodological framework for the development of a guideline for establishing a regulatory science system for supervising the application of artificial intelligence for traditional Chinese medicine (TCM). It introduced all of the key steps for developing the guideline as follows: the composition of the guideline expert groups, summary steps, agency, purpose, targeted population, writing, publishing, updating, dissemination, dynamic monitoring, and evaluation. The guideline will provide the basis for national authorities to effectively regulate artificial intelligence technology and enrich the supervisory system for TCM, and it will be of great significance to TCM.

Identifiers

PMID35692572
PMCPMC9184203
OpenAlexW4281621454

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.