Machine learning in TCM with natural products and molecules: current status and future perspectives
Abstract Traditional Chinese medicine (TCM) has been practiced for thousands of years with clinical efficacy. Natural products and their effective agents such as artemisinin and paclitaxel have saved millions of lives worldwide. Artificial intelligence is being increasingly deployed in TCM. By summa...
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| Format: | Article |
| Language: | English |
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BMC
2023-04-01
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| Series: | Chinese Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13020-023-00741-9 |
| _version_ | 1827961126562824192 |
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| author | Suya Ma Jinlei Liu Wenhua Li Yongmei Liu Xiaoshan Hui Peirong Qu Zhilin Jiang Jun Li Jie Wang |
| author_facet | Suya Ma Jinlei Liu Wenhua Li Yongmei Liu Xiaoshan Hui Peirong Qu Zhilin Jiang Jun Li Jie Wang |
| author_sort | Suya Ma |
| collection | DOAJ |
| description | Abstract Traditional Chinese medicine (TCM) has been practiced for thousands of years with clinical efficacy. Natural products and their effective agents such as artemisinin and paclitaxel have saved millions of lives worldwide. Artificial intelligence is being increasingly deployed in TCM. By summarizing the principles and processes of deep learning and traditional machine learning algorithms, analyzing the application of machine learning in TCM, reviewing the results of previous studies, this study proposed a promising future perspective based on the combination of machine learning, TCM theory, chemical compositions of natural products, and computational simulations based on molecules and chemical compositions. In the first place, machine learning will be utilized in the effective chemical components of natural products to target the pathological molecules of the disease which could achieve the purpose of screening the natural products on the basis of the pathological mechanisms they target. In this approach, computational simulations will be used for processing the data for effective chemical components, generating datasets for analyzing features. In the next step, machine learning will be used to analyze the datasets on the basis of TCM theories such as the superposition of syndrome elements. Finally, interdisciplinary natural product-syndrome research will be established by unifying the results of the two steps outlined above, potentially realizing an intelligent artificial intelligence diagnosis and treatment model based on the effective chemical components of natural products under the guidance of TCM theory. This perspective outlines an innovative application of machine learning in the clinical practice of TCM based on the investigation of chemical molecules under the guidance of TCM theory. |
| first_indexed | 2024-04-09T16:21:56Z |
| format | Article |
| id | doaj.art-bd13cf3e43a14b9faa7baaee5360d9cc |
| institution | Directory Open Access Journal |
| issn | 1749-8546 |
| language | English |
| last_indexed | 2024-04-09T16:21:56Z |
| publishDate | 2023-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Chinese Medicine |
| spelling | doaj.art-bd13cf3e43a14b9faa7baaee5360d9cc2023-04-23T11:28:04ZengBMCChinese Medicine1749-85462023-04-0118111710.1186/s13020-023-00741-9Machine learning in TCM with natural products and molecules: current status and future perspectivesSuya Ma0Jinlei Liu1Wenhua Li2Yongmei Liu3Xiaoshan Hui4Peirong Qu5Zhilin Jiang6Jun Li7Jie Wang8Guang’anmen Hospital, China Academy of Chinese Medicine SciencesGuang’anmen Hospital, China Academy of Chinese Medicine SciencesTianjin University of Traditional Chinese MedicineGuang’anmen Hospital, China Academy of Chinese Medicine SciencesGuang’anmen Hospital, China Academy of Chinese Medicine SciencesGuang’anmen Hospital, China Academy of Chinese Medicine SciencesGuang’anmen Hospital, China Academy of Chinese Medicine SciencesGuang’anmen Hospital, China Academy of Chinese Medicine SciencesGuang’anmen Hospital, China Academy of Chinese Medicine SciencesAbstract Traditional Chinese medicine (TCM) has been practiced for thousands of years with clinical efficacy. Natural products and their effective agents such as artemisinin and paclitaxel have saved millions of lives worldwide. Artificial intelligence is being increasingly deployed in TCM. By summarizing the principles and processes of deep learning and traditional machine learning algorithms, analyzing the application of machine learning in TCM, reviewing the results of previous studies, this study proposed a promising future perspective based on the combination of machine learning, TCM theory, chemical compositions of natural products, and computational simulations based on molecules and chemical compositions. In the first place, machine learning will be utilized in the effective chemical components of natural products to target the pathological molecules of the disease which could achieve the purpose of screening the natural products on the basis of the pathological mechanisms they target. In this approach, computational simulations will be used for processing the data for effective chemical components, generating datasets for analyzing features. In the next step, machine learning will be used to analyze the datasets on the basis of TCM theories such as the superposition of syndrome elements. Finally, interdisciplinary natural product-syndrome research will be established by unifying the results of the two steps outlined above, potentially realizing an intelligent artificial intelligence diagnosis and treatment model based on the effective chemical components of natural products under the guidance of TCM theory. This perspective outlines an innovative application of machine learning in the clinical practice of TCM based on the investigation of chemical molecules under the guidance of TCM theory.https://doi.org/10.1186/s13020-023-00741-9Machine learningDeep learningTraditional Chinese medicineNatural productsChemical componentsMultidisciplinary intersection |
| spellingShingle | Suya Ma Jinlei Liu Wenhua Li Yongmei Liu Xiaoshan Hui Peirong Qu Zhilin Jiang Jun Li Jie Wang Machine learning in TCM with natural products and molecules: current status and future perspectives Chinese Medicine Machine learning Deep learning Traditional Chinese medicine Natural products Chemical components Multidisciplinary intersection |
| title | Machine learning in TCM with natural products and molecules: current status and future perspectives |
| title_full | Machine learning in TCM with natural products and molecules: current status and future perspectives |
| title_fullStr | Machine learning in TCM with natural products and molecules: current status and future perspectives |
| title_full_unstemmed | Machine learning in TCM with natural products and molecules: current status and future perspectives |
| title_short | Machine learning in TCM with natural products and molecules: current status and future perspectives |
| title_sort | machine learning in tcm with natural products and molecules current status and future perspectives |
| topic | Machine learning Deep learning Traditional Chinese medicine Natural products Chemical components Multidisciplinary intersection |
| url | https://doi.org/10.1186/s13020-023-00741-9 |
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