scholarly journals Standardization of Syndrome Differentiation Defined by Traditional Chinese Medicine in Operative Breast Cancer: A Modified Delphi Study

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Qianqian Guo ◽  
Qianjun Chen
Keyword(s):  
Breast Cancer ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Delphi Method ◽  
Delphi Study ◽  
Literature Search ◽  
Syndrome Differentiation ◽  
Response Ratio ◽  
Modified Delphi ◽  
E Mail

Objective. The aim of this study was to establish the standardization of syndrome differentiation of operative breast cancer treated with Traditional Chinese Medicine (TCM) by the modified Delphi method.Method. A literature search for standardization of syndrome differentiation of operative breast cancer was conducted and eligible articles were identified in indexed databases from 1982 to 2013. We carried out two rounds of investigation between March and October 2013 and organized 20 experts who focused on TCM or integrative medicine in breast cancer research. Experts’ judgments were collectedviaposted questionnaires or e-mail. A final evaluation was carried out after the end of both rounds.Result. The response ratio of the 1st round investigation reached 100%, and two experts were excluded due to the uncompleted questionnaire. The 2nd round investigation was completed by 18 experts in the 1st round panel board. In both rounds, the experts agreed that the stage of breast cancer defined by TCM could be divided into the perioperation period, the perichemotherapy period, the periradiotherapy period, and the consolidation period.Conclusion. We identified the feasibility and reasonability to establish the standardization of syndrome differentiation of operative breast cancer. According to the suggestions from experts in our Delphi study, we preliminarily established the TCM standard of syndrome differentiation based on different treatment stages of operative breast cancer.

scholarly journals Intra-Rater and Inter-Rater Reliability of Tongue Coating Diagnosis in Traditional Chinese Medicine Using Smartphones: Quasi-Delphi Study

10.2196/16018 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e16018 ◽  
Author(s):  
Zhi Chun Wang ◽  
Shi Ping Zhang ◽  
Pong Chi Yuen ◽  
Kam Wa Chan ◽  
Yi Yi Chan ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Delphi Method ◽  
Delphi Study ◽  
Classification Scheme ◽  
Tongue Coating ◽  
Rater Reliability ◽  
Tongue Diagnosis ◽  
Image Inspection ◽  
Image Set

Background There is a growing trend in the use of mobile health (mHealth) technologies in traditional Chinese medicine (TCM) and telemedicine, especially during the coronavirus disease (COVID-19) outbreak. Tongue diagnosis is an important component of TCM, but also plays a role in Western medicine, for example in dermatology. However, the procedure of obtaining tongue images has not been standardized and the reliability of tongue diagnosis by smartphone tongue images has yet to be evaluated. Objective The first objective of this study was to develop an operating classification scheme for tongue coating diagnosis. The second and main objective of this study was to determine the intra-rater and inter-rater reliability of tongue coating diagnosis using the operating classification scheme. Methods An operating classification scheme for tongue coating was developed using a stepwise approach and a quasi-Delphi method. First, tongue images (n=2023) were analyzed by 2 groups of assessors to develop the operating classification scheme for tongue coating diagnosis. Based on clinicians’ (n=17) own interpretations as well as their use of the operating classification scheme, the results of tongue diagnosis on a representative tongue image set (n=24) were compared. After gathering consensus for the operating classification scheme, the clinicians were instructed to use the scheme to assess tongue features of their patients under direct visual inspection. At the same time, the clinicians took tongue images of the patients with smartphones and assessed tongue features observed in the smartphone image using the same classification scheme. The intra-rater agreements of these two assessments were calculated to determine which features of tongue coating were better retained by the image. Using the finalized operating classification scheme, clinicians in the study group assessed representative tongue images (n=24) that they had taken, and the intra-rater and inter-rater reliability of their assessments was evaluated. Results Intra-rater agreement between direct subject inspection and tongue image inspection was good to very good (Cohen κ range 0.69-1.0). Additionally, when comparing the assessment of tongue images on different days, intra-rater reliability was good to very good (κ range 0.7-1.0), except for the color of the tongue body (κ=0.22) and slippery tongue fur (κ=0.1). Inter-rater reliability was moderate for tongue coating (Gwet AC2 range 0.49-0.55), and fair for color and other features of the tongue body (Gwet AC2=0.34). Conclusions Taken together, our study has shown that tongue images collected via smartphone contain some reliable features, including tongue coating, that can be used in mHealth analysis. Our findings thus support the use of smartphones in telemedicine for detecting changes in tongue coating.

scholarly journals Intra-Rater and Inter-Rater Reliability of Tongue Coating Diagnosis in Traditional Chinese Medicine Using Smartphones: Quasi-Delphi Study (Preprint)

2019 ◽  
Author(s):  
Zhi Chun Wang ◽  
Shi Ping Zhang ◽  
Pong Chi Yuen ◽  
Kam Wa Chan ◽  
Yi Yi Chan ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Delphi Method ◽  
Delphi Study ◽  
Classification Scheme ◽  
Tongue Coating ◽  
Rater Reliability ◽  
Tongue Diagnosis ◽  
Image Inspection ◽  
Image Set

BACKGROUND There is a growing trend in the use of mobile health (mHealth) technologies in traditional Chinese medicine (TCM) and telemedicine, especially during the coronavirus disease (COVID-19) outbreak. Tongue diagnosis is an important component of TCM, but also plays a role in Western medicine, for example in dermatology. However, the procedure of obtaining tongue images has not been standardized and the reliability of tongue diagnosis by smartphone tongue images has yet to be evaluated. OBJECTIVE The first objective of this study was to develop an operating classification scheme for tongue coating diagnosis. The second and main objective of this study was to determine the intra-rater and inter-rater reliability of tongue coating diagnosis using the operating classification scheme. METHODS An operating classification scheme for tongue coating was developed using a stepwise approach and a quasi-Delphi method. First, tongue images (n=2023) were analyzed by 2 groups of assessors to develop the operating classification scheme for tongue coating diagnosis. Based on clinicians’ (n=17) own interpretations as well as their use of the operating classification scheme, the results of tongue diagnosis on a representative tongue image set (n=24) were compared. After gathering consensus for the operating classification scheme, the clinicians were instructed to use the scheme to assess tongue features of their patients under direct visual inspection. At the same time, the clinicians took tongue images of the patients with smartphones and assessed tongue features observed in the smartphone image using the same classification scheme. The intra-rater agreements of these two assessments were calculated to determine which features of tongue coating were better retained by the image. Using the finalized operating classification scheme, clinicians in the study group assessed representative tongue images (n=24) that they had taken, and the intra-rater and inter-rater reliability of their assessments was evaluated. RESULTS Intra-rater agreement between direct subject inspection and tongue image inspection was good to very good (Cohen κ range 0.69-1.0). Additionally, when comparing the assessment of tongue images on different days, intra-rater reliability was good to very good (κ range 0.7-1.0), except for the color of the tongue body (κ=0.22) and slippery tongue fur (κ=0.1). Inter-rater reliability was moderate for tongue coating (Gwet AC2 range 0.49-0.55), and fair for color and other features of the tongue body (Gwet AC2=0.34). CONCLUSIONS Taken together, our study has shown that tongue images collected via smartphone contain some reliable features, including tongue coating, that can be used in mHealth analysis. Our findings thus support the use of smartphones in telemedicine for detecting changes in tongue coating.

scholarly journals Machine-readable Yin–Yang imbalance: traditional Chinese medicine syndrome computer modeling based on three-dimensional noninvasive cardiac electrophysiology imaging

2019 ◽  
Vol 47 (4) ◽  
pp. 1580-1591 ◽  
Author(s):  
Wei Cen ◽  
Ralph Hoppe ◽  
Aiwu Sun ◽  
Hongyan Ding ◽  
Ning Gu
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Electrical Activity ◽  
Computer Modeling ◽  
Cardiac Electrophysiology ◽  
Three Dimensional ◽  
Mathematical Physics ◽  
Syndrome Differentiation ◽  
Physics Model ◽  
Machine Readable

Objectives The principal diagnostic methods of traditional Chinese medicine (TCM) are inspection, auscultation and olfaction, inquiry, and pulse-taking. Treatment by syndrome differentiation is likely to be subjective. This study was designed to provide a basic theory for TCM diagnosis and establish an objective means of evaluating the correctness of syndrome differentiation. Methods We herein provide the basic theory of TCM syndrome computer modeling based on a noninvasive cardiac electrophysiology imaging technique. Noninvasive cardiac electrophysiology imaging records the heart’s electrical activity from hundreds of electrodes on the patient’s torso surface and therefore provides much more information than 12-lead electrocardiography. Through mathematical reconstruction algorithm calculations, the reconstructed heart model is a machine-readable description of the underlying mathematical physics model that reveals the detailed three-dimensional (3D) electrophysiological activity of the heart. Results From part of the simulation results, the imaged 3D cardiac electrical source provides dynamic information regarding the heart’s electrical activity at any given location within the 3D myocardium. Conclusions This noninvasive cardiac electrophysiology imaging method is suitable for translating TCM syndromes into a computable format of the underlying mathematical physics model to offer TCM diagnosis evidence-based standards for ensuring correct evaluation and rigorous, scientific data for demonstrating its efficacy.

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