Evidence map›Paper›PMID 38974044›Full record

ArticleFrontiers in pharmacology2024

Possible opportunities and challenges for traditional Chinese medicine research in 2035.

Nanqu Huang, Wendi Huang, Jingjing Wu, Sheng Long, Yong Luo, Juan Huang

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  5. Evaluation of the Antibacterial Activity ofCurrent pharmaceutical design · 2026
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  7. Article
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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

6 authors.

Nanqu HuangNational Drug Clinical Trial Institution, The First People's Hospital of Zunyi, Third Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Wendi HuangNational Drug Clinical Trial Institution, The First People's Hospital of Zunyi, Third Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Jingjing WuNational Drug Clinical Trial Institution, The First People's Hospital of Zunyi, Third Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Sheng LongCloud Computing Division, Jiangsu Hoperun Software Co., Ltd., Nanjing, Jiangsu, China.
Yong LuoNational Drug Clinical Trial Institution, The First People's Hospital of Zunyi, Third Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Juan HuangKey Laboratory of Basic Pharmacology and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, Zunyi Medical University, Zunyi, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The drug development process is poised for significant transformation due to the rapid advancement of modern biological and information technologies, such as artificial intelligence (AI). As these new technologies and concepts infiltrate every stage of drug development, the efficiency and success rate of research and development are expected to improve substantially. Traditional Chinese medicine (TCM), a time-honored therapeutic system encompassing herbal medicine, acupuncture, and qigong, will also be profoundly impacted by these advancements. Over the next decade, Traditional Chinese medicine research will encounter both opportunities and challenges as it integrates with modern technologies and concepts. By 2035, TCM is anticipated to merge with modern medicine through a more contemporary and open research and development model, providing substantial support for treating a broader spectrum of diseases.

Indexed as

artificial intelligencecomplementary medicinemodern medicinepredictiontraditional Chinese medicine

Identifiers

PMID38974044
PMCPMC11224461

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.