Evidence map›Paper›PMID 34394900›Full record

ArticleJournal of healthcare engineering2021

A Core Drug Discovery Framework from Large-Scale Literature for Cold Pathogenic Disease Treatment in Traditional Chinese Medicine.

Yun Zhang, Yongguo Liu, Jiajing Zhu, Zhi Chen, Dongxiao Li, Yonghua Xiao, Xiaofeng Liu, Shuangqing Zhai

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 88% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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 4 institutions in 1 country.

Yun ZhangKnowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.ORCID 0000-0001-8716-4179
Yongguo LiuKnowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.ORCID 0000-0002-4906-7025
Jiajing ZhuKnowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.ORCID 0000-0002-5916-3141
Zhi ChenKnowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.ORCID 0000-0002-5159-1280
Dongxiao LiSichuan Academy of Chinese Medical Sciences, Chengdu 610041, China.ORCID 0000-0002-1996-143X
Yonghua XiaoDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.ORCID 0000-0002-5166-315X
Xiaofeng LiuSchool of Basic Medical Science, Beijing University of Chinese Medicine, Beijing 100029, China.ORCID 0000-0003-1789-826X
Shuangqing ZhaiSchool of Basic Medical Science, Beijing University of Chinese Medicine, Beijing 100029, China.ORCID 0000-0002-7226-3577
University of Electronic Science and Technology of China · CNBeijing University of Chinese Medicine · CNDongzhimen Hospital Affiliated to Beijing University of Chinese Medicine · CNSichuan Academy of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cold pathogenic disease is a widespread disease in traditional Chinese medicine, which includes influenza and respiratory infection associated with high incidence and mortality. Discovering effective core drugs in Chinese medicine prescriptions for treating the disease and reducing patients' symptoms has attracted great interest. In this paper, we explore the core drugs for curing various syndromes of cold pathogenic disease from large-scale literature. We propose a core drug discovery framework incorporating word embedding and community detection algorithms, which contains three parts: disease corpus construction, drug network generation, and core drug discovery. First, disease corpus is established by collecting and preprocessing large-scale literature about the Chinese medicine treatment of cold pathogenic disease from China National Knowledge Infrastructure. Second, we adopt the Chinese word embedding model SSP2VEC for mining the drug implication implied in the literature; then, a drug network is established by the semantic similarity among drugs. Third, the community detection method COPRA based on label propagation is adopted to reveal drug communities and identify core drugs in the drug network. We compute the community size, closeness centrality, and degree distributions of the drug network to analyse the patterns of core drugs. We acquire 4681 literature from China national knowledge infrastructure. Twelve significant drug communities are discovered, in which the top-10 drugs in every drug community are recognized as core drugs with high accuracy, and four classical prescriptions for treating different syndromes of cold pathogenic disease are discovered. The proposed framework can identify effective core drugs for curing cold pathogenic disease, and the research can help doctors to verify the compatibility laws of Chinese medicine prescriptions.

Indexed as

Drugs, Chinese HerbalMedicine, Chinese TraditionalData MiningDrug DiscoveryHumansSyndromeDrugs, Chinese Herbal

Identifiers

PMID34394900
PMCPMC8360722
OpenAlexW3190203684

What Socratic 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 Socratic graph.