Evidence map›Paper›PMID 37083631›Full record

ArticleJMIR formative research2023

Visualization of Traditional Chinese Medicine Formulas: Development and Usability Study.

Zhiyue Wu, Suyuan Peng, Liang Zhou

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Zhiyue Wu *Institute of Medical Technology, Peking University, Beijing, China.ORCID https://orcid.org/0009-0000-6662-1537
Suyuan Peng *National Institute of Health Data Science, Peking University, Beijing, China.ORCID https://orcid.org/0000-0002-8221-7574
Liang ZhouNational Institute of Health Data Science, Peking University, Beijing, China.ORCID https://orcid.org/0000-0002-0462-4131

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditional Chinese medicine (TCM) formulas are combinations of Chinese herbal medicines. Knowledge of classic medicine formulas is the basis of TCM diagnosis and treatment and is the core of TCM inheritance. The large number and flexibility of medicine formulas make memorization difficult, and understanding their composition rules is even more difficult. The multifaceted and multidimensional properties of herbal medicines are important for understanding the formula; however, these are usually separated from the formula information. Furthermore, these data are presented as text and cannot be analyzed jointly and interactively.

objectiveWe aimed to devise a visualization method for TCM formulas that shows the composition of medicine formulas and the multidimensional properties of herbal medicines involved and supports the comparison of medicine formulas.

methodsA TCM formula visualization method with multiple linked views is proposed and implemented as a web-based tool after close collaboration between visualization and TCM experts. The composition of medicine formulas is visualized in a formula view with a similarity-based layout supporting the comparison of compositing herbs; a shared herb view complements the formula view by showing all overlaps of pair-wise formulas; and a dimensionality-reduction plot of herbs enables the visualization of multidimensional herb properties. The usefulness of the tool was evaluated through a usability study with TCM experts.

resultsOur method was applied to 2 typical categories of medicine formulas, namely tonic formulas and heat-clearing formulas, which contain 20 and 26 formulas composed of 58 and 73 herbal medicines, respectively. Each herbal medicine has a 23-dimensional characterizing attribute. In the usability study, TCM experts explored the 2 data sets with our web-based tool and quickly gained insight into formulas and herbs of interest, as well as the overall features of the formula groups that are difficult to identify with the traditional text-based method. Moreover, feedback from the experts indicated the usefulness of the proposed method.

conclusionsOur TCM formula visualization method is able to visualize and compare complex medicine formulas and the multidimensional attributes of herbal medicines using a web-based tool. TCM experts gained insights into 2 typical medicine formula categories using our method. Overall, the new method is a promising first step toward new TCM formula education and analysis methodologies.

Indexed as

Chinese medicine formulasfive elementsinteractive data analysismultifaceted data visualizationtraditional Chinese medicinevisualization

Identifiers

PMID37083631
PMCPMC10163399

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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.