Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population
Abstract Background Fatigue is a kind of non-specific symptom, which occurs widely in sub-health and various diseases. It is closely related to people's physical and mental health. Due to the lack of objective diagnostic criteria, it is often neglected in clinical diagnosis, especially in the e...
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| Format: | Article |
| Language: | English |
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BMC
2021-02-01
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| Series: | BMC Medical Informatics and Decision Making |
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| Online Access: | https://doi.org/10.1186/s12911-021-01410-3 |
| _version_ | 1818914127347712000 |
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| author | Yulin Shi Xiaojuan Hu Ji Cui Longtao Cui Jingbin Huang Xuxiang Ma Tao Jiang Xinghua Yao Fang Lan Jun Li Zijuan Bi Jiacai Li Yu Wang Hongyuan Fu Jue Wang Yanting Lin Jingxuan Bai Xiaojing Guo Liping Tu Jiatuo Xu |
| author_facet | Yulin Shi Xiaojuan Hu Ji Cui Longtao Cui Jingbin Huang Xuxiang Ma Tao Jiang Xinghua Yao Fang Lan Jun Li Zijuan Bi Jiacai Li Yu Wang Hongyuan Fu Jue Wang Yanting Lin Jingxuan Bai Xiaojing Guo Liping Tu Jiatuo Xu |
| author_sort | Yulin Shi |
| collection | DOAJ |
| description | Abstract Background Fatigue is a kind of non-specific symptom, which occurs widely in sub-health and various diseases. It is closely related to people's physical and mental health. Due to the lack of objective diagnostic criteria, it is often neglected in clinical diagnosis, especially in the early stage of disease. Many clinical practices and researches have shown that tongue and pulse conditions reflect the body's overall state. Establishing an objective evaluation method for diagnosing disease fatigue and non-disease fatigue by combining clinical symptom, index, and tongue and pulse data is of great significance for clinical treatment timely and effectively. Methods In this study, 2632 physical examination population were divided into healthy controls, sub-health fatigue group, and disease fatigue group. Complex network technology was used to screen out core symptoms and Western medicine indexes of sub-health fatigue and disease fatigue population. Pajek software was used to construct core symptom/index network and core symptom-index combined network. Simultaneously, canonical correlation analysis was used to analyze the objective tongue and pulse data between the two groups of fatigue population and analyze the distribution of tongue and pulse data. Results Some similarities were found in the core symptoms of sub-health fatigue and disease fatigue population, but with different node importance. The node-importance difference indicated that the diagnostic contribution rate of the same symptom to the two groups was different. The canonical correlation coefficient of tongue and pulse data in the disease fatigue group was 0.42 (P < 0.05), on the contrast, correlation analysis of tongue and pulse in the sub-health fatigue group showed no statistical significance. Conclusions The complex network technology was suitable for correlation analysis of symptoms and indexes in fatigue population, and tongue and pulse data had a certain diagnostic contribution to the classification of fatigue population. |
| first_indexed | 2024-12-19T23:41:26Z |
| format | Article |
| id | doaj.art-a3d5923b5b6d4bed9e510ec08b8d4eb0 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-19T23:41:26Z |
| publishDate | 2021-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-a3d5923b5b6d4bed9e510ec08b8d4eb02022-12-21T20:01:24ZengBMCBMC Medical Informatics and Decision Making1472-69472021-02-0121111410.1186/s12911-021-01410-3Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue populationYulin Shi0Xiaojuan Hu1Ji Cui2Longtao Cui3Jingbin Huang4Xuxiang Ma5Tao Jiang6Xinghua Yao7Fang Lan8Jun Li9Zijuan Bi10Jiacai Li11Yu Wang12Hongyuan Fu13Jue Wang14Yanting Lin15Jingxuan Bai16Xiaojing Guo17Liping Tu18Jiatuo Xu19Basic Medical College, Shanghai University of Traditional Chinese MedicineShanghai Innovation Center of TCM Health Service, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineBasic Medical College, Shanghai University of Traditional Chinese MedicineAbstract Background Fatigue is a kind of non-specific symptom, which occurs widely in sub-health and various diseases. It is closely related to people's physical and mental health. Due to the lack of objective diagnostic criteria, it is often neglected in clinical diagnosis, especially in the early stage of disease. Many clinical practices and researches have shown that tongue and pulse conditions reflect the body's overall state. Establishing an objective evaluation method for diagnosing disease fatigue and non-disease fatigue by combining clinical symptom, index, and tongue and pulse data is of great significance for clinical treatment timely and effectively. Methods In this study, 2632 physical examination population were divided into healthy controls, sub-health fatigue group, and disease fatigue group. Complex network technology was used to screen out core symptoms and Western medicine indexes of sub-health fatigue and disease fatigue population. Pajek software was used to construct core symptom/index network and core symptom-index combined network. Simultaneously, canonical correlation analysis was used to analyze the objective tongue and pulse data between the two groups of fatigue population and analyze the distribution of tongue and pulse data. Results Some similarities were found in the core symptoms of sub-health fatigue and disease fatigue population, but with different node importance. The node-importance difference indicated that the diagnostic contribution rate of the same symptom to the two groups was different. The canonical correlation coefficient of tongue and pulse data in the disease fatigue group was 0.42 (P < 0.05), on the contrast, correlation analysis of tongue and pulse in the sub-health fatigue group showed no statistical significance. Conclusions The complex network technology was suitable for correlation analysis of symptoms and indexes in fatigue population, and tongue and pulse data had a certain diagnostic contribution to the classification of fatigue population.https://doi.org/10.1186/s12911-021-01410-3FatigueComplex networkSymptomIndexTongue and pulse data |
| spellingShingle | Yulin Shi Xiaojuan Hu Ji Cui Longtao Cui Jingbin Huang Xuxiang Ma Tao Jiang Xinghua Yao Fang Lan Jun Li Zijuan Bi Jiacai Li Yu Wang Hongyuan Fu Jue Wang Yanting Lin Jingxuan Bai Xiaojing Guo Liping Tu Jiatuo Xu Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population BMC Medical Informatics and Decision Making Fatigue Complex network Symptom Index Tongue and pulse data |
| title | Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population |
| title_full | Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population |
| title_fullStr | Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population |
| title_full_unstemmed | Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population |
| title_short | Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population |
| title_sort | clinical data mining on network of symptom and index and correlation of tongue pulse data in fatigue population |
| topic | Fatigue Complex network Symptom Index Tongue and pulse data |
| url | https://doi.org/10.1186/s12911-021-01410-3 |
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