Quality assessment of traditional Chinese medicine based on data fusion combined with machine learning: A review

Ding, Rong; Yu, Lianhui; Wang, Chenghui; Zhong, Shihong; Gu, Rui

doi:10.1080/10408347.2023.2189477

Cited by 11 publications

(5 citation statements)

References 141 publications

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“…It is not sufficient to judge the quality of TCM based on the characteristics of its constituents alone. Therefore, fusion technologies that combine multiple sources of information can be incredibly useful in TCM research, allowing us to understand the relationship between herbal samples in multiple aspects using data from different analytical instruments [ 125 ]. In addition, the application of computational bioinformatics models, such as probabilistic models and deep learning models, simplifies complex TCM data to some extent and makes them easy to understand [ 126 ].…”

Section: Discussionmentioning

confidence: 99%

Chinmedomics: a potent tool for the evaluation of traditional Chinese medicine efficacy and identification of its active components

Wang,

Yin,

Kong

et al. 2024

Chin Med

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As an important part of medical science, Traditional Chinese Medicine (TCM) attracts much public attention due to its multi-target and multi-pathway characteristics in treating diseases. However, the limitations of traditional research methods pose a dilemma for the evaluation of clinical efficacy, the discovery of active ingredients and the elucidation of the mechanism of action. Therefore, innovative approaches that are in line with the characteristics of TCM theory and clinical practice are urgently needed. Chinmendomics, a newly emerging strategy for evaluating the efficacy of TCM, is proposed. This strategy combines systems biology, serum pharmacochemistry of TCM and bioinformatics to evaluate the efficacy of TCM with a holistic view by accurately identifying syndrome biomarkers and monitoring their complex metabolic processes intervened by TCM, and finding the agents associated with the metabolic course of pharmacodynamic biomarkers by constructing a bioinformatics-based correlation network model to further reveal the interaction between agents and pharmacodynamic targets. In this article, we review the recent progress of Chinmedomics to promote its application in the modernisation and internationalisation of TCM.

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Section: Discussionmentioning

confidence: 99%

Chinmedomics: a potent tool for the evaluation of traditional Chinese medicine efficacy and identification of its active components

Wang,

Yin,

Kong

et al. 2024

Chin Med

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“…Data fusion techniques are methods of joining multiple data sources to obtain more accurate and comprehensive information. Its advantage is that the data can be separated from the original analysis techniques and other independent data to build a new model and use it for the calculation and speculation of the results [ 5 ], which can be applied qualitatively and quantitatively. As a technology with more accurate judgment and higher precision, data fusion is commonly used in automation [ 6 ], the mining industry [ 7 ], aerospace [ 8 , 9 , 10 ], military technology [ 11 ], agriculture [ 12 ], and medical science [ 13 ], etc.…”

Section: Data Fusion Technologymentioning

confidence: 99%

Application of Data Fusion in Traditional Chinese Medicine: A Review

Huang,

Ma,

Dai

et al. 2023

Sensors

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Traditional Chinese medicine is characterized by numerous chemical constituents, complex components, and unpredictable interactions among constituents. Therefore, a single analytical technique is usually unable to obtain comprehensive chemical information. Data fusion is an information processing technology that can improve the accuracy of test results by fusing data from multiple devices, which has a broad application prospect by utilizing chemometrics methods, adopting low-level, mid-level, and high-level data fusion techniques, and establishing final classification or prediction models. This paper summarizes the current status of the application of data fusion strategies based on spectroscopy, mass spectrometry, chromatography, and sensor technologies in traditional Chinese medicine (TCM) in light of the latest research progress of data fusion technology at home and abroad. It also gives an outlook on the development of data fusion technology in TCM analysis to provide references for the research and development of TCM.

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“…However, the discovery of natural sports supplements from herbal medicines was serendipitous without extensive screening of the associated bioactivity. Recent advancements in the field of herbal medicine have seen a growing emphasis on the development of machine learning which encompasses a range of applications, including quality control, identification of geographic origins, pharmacodynamic material basis, medicinal properties, and pharmacokinetics and pharmacodynamics. , Furthermore, machine learning methods are being utilized to uncover active compounds within herbal medicines, predict their pharmacological activities, and assess potential therapeutic effects. , These innovative approaches not only offer new insights into the mechanisms of action of herbal medicines but also provide valuable tools for drug discovery. Therefore, developing prediction models derived via machine learning is essential in screening bioactive components of herbal medicines as potential sports supplements.…”

Section: Introductionmentioning

confidence: 99%

Identification of Active Components for Sports Supplements: Machine Learning-Driven Classification and Cell-Based Validation

Ji,

Li,

Liu

et al. 2024

ACS Omega

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The identification of active components is critical for the development of sports supplements. However, highthroughput screening of active components remains a challenge. This study sought to construct prediction models to screen active components from herbal medicines via machine learning and validate the screening by using cell-based assays. The six constructed models had an accuracy of >0.88. Twelve randomly selected active components from the screening were tested for their active potency on C2C12 cells, and 11 components induced a significant increase in myotube diameters and protein synthesis. The effect and mechanism of luteolin among the 11 active components as potential sports supplements were then investigated by using immunofluorescence staining and high-content imaging analysis. It showed that luteolin increased the skeletal muscle performance via the activation of PGC-1α and MAPK signaling pathways. Thus, high-throughput prediction models can be effectively used to screen active components as sports supplements.

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Quality assessment of traditional Chinese medicine based on data fusion combined with machine learning: A review

Cited by 11 publications

References 141 publications

Chinmedomics: a potent tool for the evaluation of traditional Chinese medicine efficacy and identification of its active components

Chinmedomics: a potent tool for the evaluation of traditional Chinese medicine efficacy and identification of its active components

Application of Data Fusion in Traditional Chinese Medicine: A Review

Identification of Active Components for Sports Supplements: Machine Learning-Driven Classification and Cell-Based Validation

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