FOLLOWUS
1. Clinical Evaluation Center, Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences,Beijing,China
2. China Academy of Chinese Medical Sciences,Beijing,China
3. Infectious Disease Clinics and Research Centers, People’s Liberation Army Hospital,Beijing,China,302
4. Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences,Beijing,China
纸质出版日期:2014,
网络出版日期:2013-10-30,
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Zhao, Yf., He, Ly., Liu, By. et al. Syndrome classification based on manifold ranking for viral hepatitis., Chin. J. Integr. Med. 20, 394–399 (2014). https://doi.org/10.1007/s11655-013-1659-4
Yu-feng Zhao, Li-yun He, Bao-yan Liu, et al. Syndrome classification based on manifold ranking for viral hepatitis[J]. Chinese Journal of Integrative Medicine, 2014,20(5):394-399.
Zhao, Yf., He, Ly., Liu, By. et al. Syndrome classification based on manifold ranking for viral hepatitis., Chin. J. Integr. Med. 20, 394–399 (2014). https://doi.org/10.1007/s11655-013-1659-4 DOI:
Yu-feng Zhao, Li-yun He, Bao-yan Liu, et al. Syndrome classification based on manifold ranking for viral hepatitis[J]. Chinese Journal of Integrative Medicine, 2014,20(5):394-399. DOI: 10.1007/s11655-013-1659-4.
Treatment determination based on syndrome differentiation is the key of Chinese medicine. A feasible way of improving the clinical therapy effectiveness is needed to correctly differentiate the syndrome classifications based on the clinical manifestations. In this paper
a novel data mining method based on manifold ranking (MR) is proposed to explore the relation between syndromes and symptoms for viral hepatitis. Since MR could take the symptom data with expert differentiation and the symptom data without expert differentiation into the task of syndrome classification
the clinical information used for modeling the syndrome features is greatly enlarged so as to improve the precise of syndrome classification. In addition
the proposed method of syndrome classification could also avoid two disadvantages in previous methods: linear relation of the clinical data and mutually exclusive symptoms among different syndromes. And it could help exploit the latent relation between syndromes and symptoms more effectively. Better performance of syndrome classification is able to be achieved according to the experimental results and the clinical experts.
Treatment determination based on syndrome differentiation is the key of Chinese medicine. A feasible way of improving the clinical therapy effectiveness is needed to correctly differentiate the syndrome classifications based on the clinical manifestations. In this paper
a novel data mining method based on manifold ranking (MR) is proposed to explore the relation between syndromes and symptoms for viral hepatitis. Since MR could take the symptom data with expert differentiation and the symptom data without expert differentiation into the task of syndrome classification
the clinical information used for modeling the syndrome features is greatly enlarged so as to improve the precise of syndrome classification. In addition
the proposed method of syndrome classification could also avoid two disadvantages in previous methods: linear relation of the clinical data and mutually exclusive symptoms among different syndromes. And it could help exploit the latent relation between syndromes and symptoms more effectively. Better performance of syndrome classification is able to be achieved according to the experimental results and the clinical experts.
Chinese Medicinesyndrome classificationdata miningmanifold ranking
Chinese Medicinesyndrome classificationdata miningmanifold ranking
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