Evidence map›Paper›PMID 37693890›Full record

ReviewFrontiers in pharmacology2023

Application of digital-intelligence technology in the processing of Chinese materia medica.

Wanlong Zhang, Changhua Zhang, Lan Cao, Fang Liang, Weihua Xie, Liang Tao, Chen Chen, Ming Yang, Lingyun Zhong

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. 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

9 authors.

Wanlong Zhang *College of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China.
Changhua Zhang *College of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China.
Lan CaoCollege of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China.
Fang LiangCollege of Physical Culture, Yuzhang Normal University, Nanchang, Jiangxi, China.
Weihua XieCollege of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China.
Liang TaoNanchang Research Institute, Sun Yat-sen University, Nanchang, Jiangxi, China.
Chen ChenSchool of Biomedical Sciences, University of Queensland, Brisbane, QLD, Australia.
Ming YangKey Laboratory of Modern Chinese Medicine Preparation of Ministry of Education, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China.
Lingyun ZhongCollege of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Indexed as

application progressChinese medicine processingdigital and intelligent technologiesindustrializationstandardization

Identifiers

PMID37693890
PMCPMC10484343

What OpenQuestion holds

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LicenceCC BY
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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.