Liyuan Chen^1,2,3,*, Zhenhua Luo^1,2,3, Xianhua Li^1,2,3, Ya Chen^1,2,3, Mengyu Chang⁴

Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 69-77, 2022, DOI:10.32604/jimh.2022.036288 - 05 January 2023

Abstract Objective: Explore the homogeneous management of appropriate technology for Traditional Chinese Medicine (TCM) care based on the county medical community platform. Methods: The hospital has formed a county medical community since 2020, based on which the platform develops homogeneous management of appropriate technologies for TCM nursing, establishes a medical training center, a remote consultation center and a TCM nursing quality control center, strengthens the construction of TCM nursing specialties, integrates TCM with public health and consolidates information support. The “321” model was developed, with January 2021 to December 2021 as the post-implementation period and January More >

Hai Long¹, Zhe Wang¹, Yidi Cui^2,3, Junhui Wang⁴, Bo Gao⁵, Chao Chen⁵, Yan Zhu^5,*, Heinrich Herre¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5197-5217, 2022, DOI:10.32604/cmc.2022.029365 - 28 July 2022

Abstract Psoriasis is a chronic, non-communicable, painful, disfiguring and disabling disease for which there is no cure, with great negative impact on patients’ quality of life (QoL). Diagnosis and treatment with traditional Chinese medical technique based on syndrome differentiation has been used in practice for a long time and proven effective, though, up to now, there are only a few available studies about the use of semantic technologies and the knowledge systems that use Traditional Chinese Medicine (TCM)-syndrome differentiation for information retrieval and automated reasoning. In this paper we use semantic techniques based on ontologies to… More >

Jialin Ma^1,*, Zhaojun Wang², Hai Guo³, Qian Xie^1,4, Tao Wang⁴, Bolun Chen⁵

Computer Systems Science and Engineering, Vol.40, No.3, pp. 979-993, 2022, DOI:10.32604/csse.2022.016759 - 24 September 2021

Abstract Syndrome differentiation-based treatment is one of the key characteristics of Traditional Chinese Medicine (TCM). The process of syndrome differentiation is difficult and challenging due to its complexity, diversity and vagueness. Analyzing syndrome principles from historical records of TCM using data mining (DM) technology has been of high interest in recent years. Nevertheless, in most relevant studies, existing DM algorithms have been simply developed for TCM mining, while the combination of TCM theories or its characteristics with DM algorithms has rarely been reported. This paper presents a novel Symptom-Syndrome Topic Model (SSTM), which is a supervised probabilistic More >

Yonghong Xie^{1, 3}, Liangyuan Hu^{1, 3}, Xingxing Chen^{2, 3}, Jim Feng⁴, Dezheng Zhang^{1, 3, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 481-494, 2020, DOI:10.32604/cmc.2020.010297 - 23 July 2020

Abstract As one of the most valuable assets in China, traditional medicine has a long history and contains pieces of knowledge. The diagnosis and treatment of Traditional Chinese Medicine (TCM) has benefited from the natural language processing technology. This paper proposes a knowledge-based syndrome reasoning method in computerassisted diagnosis. This method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning path. According to this reasoning path, we could infer the path from the symptoms to the More >