Syndrome Differentiation and Treatment Algorithm Model in Traditional Chinese Medicine Based on Disease Cause, Location, Characteristics and Conditions

Chen, Ju; Yang, Dianxing; Cao, Yue; Ma, Yiyi; Wen, Chuanbiao; Huang, Xiwei; Guo, Jinhong

doi:10.1109/access.2018.2881535

Cited by 6 publications

(6 citation statements)

References 11 publications

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“…It is in the exponential family and has finite dimensional sufficient statistics. It is conjugate to the multinomial distribution [ 9 ]. Mult represents the multinomial distribution.…”

Section: Methodsmentioning

confidence: 99%

“…Syndrome differentiation is a process through which doctors make a diagnosis based on subjective knowledge and experience in accord with the objective reality of a patient. Because of the differences in individuals and the limited knowledge or experience of doctors, one patient may be diagnosed with different syndromes by different doctors [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

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SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine

Gong

Wang

et al. 2022

Journal of Healthcare Engineering

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Syndrome differentiation is the most basic diagnostic method in traditional Chinese medicine (TCM). The process of syndrome differentiation is difficult and challenging due to its complexity, diversity, and vagueness. Recently, artificial intelligent methods have been introduced to discover the regularities of syndrome differentiation from TCM medical records, but the existing DM algorithms failed to consider how a syndrome is generated according to TCM theories. In this paper, we propose a novel topic model framework named syndrome differentiation topic model (SDTM) to dynamically characterize the process of syndrome differentiation. The SDTM framework utilizes latent Dirichlet allocation (LDA) to discover the latent semantic relationship between symptoms and syndromes in mass of Chinese medical records. We also use similarity measurement method to make the uninterpretable topics correspond with the labeled syndromes. Finally, Bayesian method is used in the final differentiated syndromes. Experimental results show the superiority of SDTM over existing topic models for the task of syndrome differentiation.

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“…It is in the exponential family and has finite dimensional sufficient statistics. It is conjugate to the multinomial distribution [ 9 ]. Mult represents the multinomial distribution.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine

Gong

Wang

et al. 2022

Journal of Healthcare Engineering

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“…Furthermore, the definition of the above 10 syndromes in Baidu Encyclopedia knowledge base is taken as a baseline for comparing the effect of learning syndrome differentiation patterns between SSTM and labeled LDA. The accuracy of comparison results is calculated by the follows formula: PrecisionðsdÞ ¼ countðfs 0 ;s 1 ;…s N top;sd g \ fs 0 ;s 1 ;…s N Baidu;sd gÞ N top;sd (10) In Eq. ( 10), sd represents a syndrome; s represents a symptom; N top,sd represents the number of top N symptoms selects according to the probability value about sd.…”

Section: Effectiveness Evaluation and Analysismentioning

confidence: 99%

“…This is a process of comprehensive judgment based on analysis, induction, reasoning via four-ways information diagnosis. This is also the key link for doctors to select proper prescriptions or therapies [7][8][9][10]. However, the relationship between syndromes is complex.…”

Section: Introductionmentioning

confidence: 99%

Mining Syndrome Differentiating Principles from Traditional Chinese Medicine Clinical Data

Ma¹,

Wang²,

Hai³

et al. 2022

Computer Systems Science and Engineering

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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 topic model with three-tier Bayesian structure. In the SSTM, syndromes are considered as observed topic labels to distinguish certain symptoms from possible symptoms according to their different positions. The generation of our model is in full compliance with the syndrome differentiation theory of TCM. Experimental results show that the SSTM is more effective than other models for syndrome differentiating.

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“…However, controversy regarding the effectiveness of acupuncture and its mechanisms remains. Acupuncture is generally applied on the basis of syndrome differentiation under the guidance of the holistic classical TCM theory [21,22]. It is an advantageous factor that cannot be replaced in the medical field at present.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of cerebrovascular characteristics of Parkinson’s disease treated with acupuncture based on magnetic resonance angiography

Yang

Miao

et al. 2021

Brain Science Advances

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Background: Acupuncture has become an important alternative clinical treatment for Parkinson’s disease (PD), but its efficacy and the underlying mechanisms remain debatable. Using a newly developed magnetic resonance angiography (MRA) method that has higher sensitivity for smaller and distal vessels and a novel tool that can trace vessels and extract vascular features, the immediate effects of acupuncture on intracranial vessels and blood flow in patients with PD as well as correlations with clinical outcomes were quantitatively evaluated. Methods: Fifteen PD patients received acupuncture at the Dazhui and Fengchi acupoint positions. MRA was performed before and after 30 min of treatment. The cerebral blood flow (CBF) and the length, volume, diameter, and signal intensity of the intracranial internal carotid artery (ICA) and middle cerebral artery (MCA) were measured. The Unified Parkinson’s Disease Rating Scale part III (UPDRS-III) and Visual Analogue Scale (VAS) were used to evaluate the motor symptoms and the subjective feelings of discomfort. Results: Acupuncture significantly reduced UPDRS-III and VAS scores. No significant changes were noted in the overall CBF before and after treatment. However, there was a significant extension effect on the length of the intracranial ICA and MCA and the distal MCA, and a significant increase in the number of branches of the MCA was found. Although acupuncture tended to increase the total volume of the intracranial ICA and the volume of the MCA, no statistical significance was reached. The total intensity was not altered, but the intensity and diameter of the M1 segment were significantly increased, whereas the intensity of the MCA was decreased. A positive correlation between M1 intensity changes and UPDRS-III changes was found. Conclusions: Angiographic evaluation suggested that acupuncture had a significant effect on intracranial blood vessels, which is one possible mechanism for acupuncture improving the motor symptoms of PD.

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Syndrome Differentiation and Treatment Algorithm Model in Traditional Chinese Medicine Based on Disease Cause, Location, Characteristics and Conditions

Cited by 6 publications

References 11 publications

SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine

SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine

Mining Syndrome Differentiating Principles from Traditional Chinese Medicine Clinical Data

Quantitative analysis of cerebrovascular characteristics of Parkinson’s disease treated with acupuncture based on magnetic resonance angiography

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