title: Clinical phenotype network: the underlying mechanism for personalized diagnosis and treatment of traditional Chinese medicine.
abstract: Traditional Chinese medicine (TCM) investigates the clinical diagnosis and treatment regularities in a typical schema of personalized medicine, which means that individualized patients with same diseases would obtain distinct diagnosis and optimal treatment from different TCM physicians. This principle has been recognized and adhered by TCM clinical practitioners for thousands of years. However, the underlying mechanisms of TCM personalized medicine are not fully investigated so far and remained unknown. This paper discusses framework of TCM personalized medicine in classic literatures and in real-world clinical settings, and investigates the underlying mechanisms of TCM personalized medicine from the perspectives of network medicine. Based on 246 well-designed outpatient records on insomnia, by evaluating the personal biases of manifestation observation and preferences of herb prescriptions, we noted significant similarities between each herb prescriptions and symptom similarities between each encounters. To investigate the underlying mechanisms of TCM personalized medicine, we constructed a clinical phenotype network (CPN), in which the clinical phenotype entities like symptoms and diagnoses are presented as nodes and the correlation between these entities as links. This CPN is used to investigate the promiscuous boundary of syndromes and the co-occurrence of symptoms. The small-world topological characteristics are noted in the CPN with high clustering structures, which provide insight on the rationality of TCM personalized diagnosis and treatment. The investigation on this network would help us to gain understanding on the underlying mechanism of TCM personalized medicine and would propose a new perspective for the refinement of the TCM individualized clinical skills.
authors.affiliation: School of Computer and Information Technology and Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, 100044, China, xzzhou@bjtu.edu.cn.
authors.forename: Xuezhong
authors.initials: X
authors.lastname: Zhou
authors.forename: Yubing
authors.initials: Y
authors.lastname: Li
authors.forename: Yonghong
authors.initials: Y
authors.lastname: Peng
authors.forename: Jingqing
authors.initials: J
authors.lastname: Hu
authors.forename: Runshun
authors.initials: R
authors.lastname: Zhang
authors.forename: Liyun
authors.initials: L
authors.lastname: He
authors.forename: Yinghui
authors.initials: Y
authors.lastname: Wang
authors.forename: Lijie
authors.initials: L
authors.lastname: Jiang
authors.forename: Shiyan
authors.initials: S
authors.lastname: Yan
authors.forename: Peng
authors.initials: P
authors.lastname: Li
authors.forename: Qi
authors.initials: Q
authors.lastname: Xie
authors.forename: Baoyan
authors.initials: B
authors.lastname: Liu
mesh_terms: D004365:Drugs, Chinese Herbal / Q000627:therapeutic use*; D006801:Humans; D008516:Medicine, Chinese Traditional / Q000379:methods*; D010641:Phenotype; D057285:Precision Medicine / Q000379:methods*; D007319:Sleep Initiation and Maintenance Disorders / Q000175:diagnosis* / Q000188:drug therapy*
chemical_list: D004365:Drugs, Chinese Herbal