Tsung-Lin Cheng

The Study on the Agreement between Automatic Tongue Diagnosis System and Traditional Chinese Medicine Practitioners.

Tongue diagnosis is an important practice in traditional Chinese medicine (TCM) for diagnosing diseases before determining proper means of treatments. Traditionally, it depends solely on personal knowledge and experience of the practitioner, thereby being criticized as lacking of objectivity. Currently, no research regarding intra- and inter-agreements of automatic tongue diagnosis system (ATDS) and TCM doctors has been conducted. In this study, the ATDS is developed to extract a variety of tongue features and provide practitioners with objective information to assist diagnoses. To evaluate the ATDS clinical stability, 2 sets of tongue images taken 1 hour apart from 20 patients with possible variations in lighting and extruding tongue, are employed to investigate intra-agreement of the ATDS, intra-agreement of the TCM doctors, and the inter-agreement between the ATDS and TCM doctors. The ATDS is shown to be more consistent with significantly higher intra-agreement than the TCM doctors (kappa value: 0.93 ± 0.06 versus 0.64 ± 0.13) with P < 0.001 (Students t-test). Inter-agreements between the ATDS and TCM doctors, as well as among the TCM doctors are both moderate. The high agreement of the ATDS can provide objective and reliable tongue features to facilitate doctor in making effective observation and diagnosis of specific diseases.

Visual agreement analyses of traditional chinese medicine: a multiple-dimensional scaling approach.

The study of TCM agreement in terms of a powerful statistical tool becomes critical in providing objective evaluations. Several previous studies have conducted on the issue of consistency of TCM, and the results have indicated that agreements are low. Traditional agreement measures only provide a single value which is not sufficient to justify if the agreement among several raters is strong or not. In light of this observation, a novel visual agreement analysis for TCM via multiple dimensional scaling (MDS) is proposed in this study. If there are clusters present in the raters in a latent manner, MDS can prove itself as an effective distinguisher. In this study, a group of doctors, consisting of 11 experienced TCM practitioners having clinical experience ranging from 3 to 15 years with a mean of 5.5 years from the Chinese Medicine Department at Changhua Christian Hospital (CCH) in Taiwan were asked to diagnose a total of fifteen tongue images, the Eight Principles derived from the TCM theorem. The results of statistical analysis show that, if there are clusters present in the raters in a latent manner, MDS can prove itself as an effective distinguisher.

TCM tongue diagnosis index of early-stage breast cancer.

OBJECTIVES This paper investigates discriminating tongue features to distinguish between early stage breast cancer (BC) patients and non-breast cancer individuals through non-invasive traditional Chinese medicine (TCM) tongue diagnosis. DESIGN The tongue features for 67 patients with 0 and 1 stages of BC, and 70 non-breast cancer individuals are extracted by the automatic tongue diagnosis system (ATDS). A total of nine tongue features, namely, tongue color, tongue quality, tongue fissure, tongue fur, red dot, ecchymosis, tooth mark, saliva, and tongue shape are identified for each tongue. Features extracted are further sub-divided according to the areas located, i.e., spleen-stomach, liver-gall-left, liver-gall-right, kidney, and heart-lung areas. This study focuses on deriving significant tongue features (p<0.05) to discriminate early-stage BC patients from non-breast cancer individuals. RESULTS The Mann-Whitney test shows that the amount of tongue fur (p=0.024), maximum covering area of tongue fur (p=0.009), thin tongue fur (p=0.009), the average area of red dot (p=0.049), the maximum area of red dot (p=0.009), red dot in the spleen-stomach area (p=0.000), and red dot in the heart-lung area (p=0.000) demonstrate significant differences. The data collected are further classified into two groups. The training group consists of 57 early-stage BC patients and 60 non-breast cancer individuals, while the testing group is composed of 10 early-stage BC patients and 10 non-breast cancer individuals. The logistic regression by utilizing these 7 tongue features with significant differences in Mann-Whitney test as factors is performed. In order to reduce the number of tongue features employed in prediction, tongue features with the least amount of significant difference, namely, maximum area of red dot and average area of red dot, are removed progressively. The tongue features of the testing group are employed in the aforementioned three models to test the power of significant tongue features identified in predicting early-stage BC. An accuracy of 80%, 80% and 90% is reached on non-breast cancer individuals by applying the 7, 6 and 5 significant tongue features obtained through Mann-Whitney test, respectively, while 60%, 60% and 50% is reached on the corresponding early-stage BC patients. CONCLUSION The TCM tongue diagnosis can serve as a preliminary screening procedure in the early detection of BC in light of its simple and non-invasive nature, followed by other more accurate testing process. To the best of our knowledge, this is the first attempt in applying non-invasive TCM tongue diagnosis to the discrimination of early-stage BC patients and non-breast cancer individuals.

Breast cancer index: a perspective on tongue diagnosis in traditional chinese medicine.

Breast cancer (BC) ranks second in the cancer fatality rate among females worldwide. Mammogram, ultrasound, magnetic resonance imaging (MRI), blood testing, and fine needle aspiration biopsy are usually applied to discriminate BC patients from normal persons. False-negative results, undetectable calcifications, movement-incurred blurry image, infection, and sampling error are commonly associated with these traditional means of diagnosis. Traditional Chinese medicine (TCM) covers a broad range of medical practices sharing common theoretical concepts. Tongue diagnosis plays an important role in TCM. Organ conditions, properties, and variation of pathogens can be revealed through observation of tongue. In light of this observation, this paper investigates discriminating tongue features to distinguish between BC patients and normal people, and establishes differentiating index to facilitate the non-invasive detection of BC. The tongue features for 60 BC patients and 70 normal persons were extracted by the Automatic Tongue Diagnosis System (ATDS). The Mann-Whitney test showed that the amount of tongue fur (P = 0.007), tongue fur in the spleen-stomach area, maximum covering area of tongue fur, thin tongue fur, the number of tooth marks, the number of red dots, red dot in the spleen-stomach area, red dot in the liver-gall-left area, red dot in the liver-gall-right area, and red dot in the heart-lung area demonstrated significant differences (P < 0.05). The tongue features of the testing group were employed to test the power of significant tongue features identified in predicting BC. An accuracy of 80% was reached by applying the seven significant tongue features obtained through Mann-Whitney test. To the best of our knowledge, this is the first attempt in applying TCM tongue diagnosis to the discrimination of BC patients and normal persons.

Analysis of agreement on traditional chinese medical diagnostics for many practitioners.

In Traditional Chinese Medicine (TCM) diagnostics, it is an important issue to study the degree of agreement among several distinct practitioners. In order to study the reliability of TCM diagnostics, we have to design an experiment to simultaneously deal with both of the cases when the data is ordinal and when there are many TCM practitioners. In this study, we consider a reliability measure called “Krippendorffs alpha” to investigate the agreement of tongue diagnostics in TCM. Besides, since it is not easy to obtain a large data set with patients rated simultaneously by many TCM practitioners, we use the renowned “bootstrapping” to obtain a 95% confidence interval for the Krippendorffs alpha. The estimated Krippendorffs alpha for the agreement among ten physicians that discerned fifteen randomly chosen patients is 0.7343, and the 95% bootstrapping confidence interval for the true alpha coefficient is [0.6570, 0.7349]. The data was collected and analyzed at the Department of Traditional Chinese Medicine, Changhua Christian Hospital (CCH) in Taiwan.

P02.34. Therapeutic effects of traditional Chinese medicine in cancer patients undergoing chemotherapy or radiotherapy: randomized, double-blind controlled trial

Purpose Cancer is one of the most major health issues worldwide. An increasing number of cancer patients received surgery, chemotherapy and radiotherapy. However, there usually exists some side-effects. Traditional Chinese Medicine (TCM) is one of the most common complementary therapies used in Taiwan. We designed a randomized, doubleblind and placebo-controlled clinical trial to evaluate the role of TCM on patients with cancer.

P02.78. Treating pediatric asthma with holistic approaches of traditional Chinese medicine.

Purpose Asthma is a chronic disease increasingly found in children. In order to find more economical and efficient alternatives to treat pediatric asthma, the Bureau of National Health Insurance of Taiwan launched the Traditional Chinese Medicine Holistic Treatment Program (TCMHTP). Based on the data collected during the program, we evaluated the effect of TCM holistic treatments on pediatric asthma.

Traditional Chinese Medicine Tongue Diagnosis Index of Early-Stage Breast Cancer

This paper investigates discriminating tongue features to distinguish between early stage BC patients and normal persons via non-invaded methods, expecting to detect BC in the early stage and give treatment in time to increase the recovery rate and lower relapse rate. The tongue features for 67 breast cancer patients of 0 and 1 stages, and 70 normal persons are extracted by the Automatic Tongue Diagnosis System (ATDS) [4-6, 28-31]. A total of nine tongue features, namely, tongue color, tongue quality, tongue fissure, tongue fur, red dot, ecchymosis, tooth mark, saliva, and tongue shape are identified for each tongue. Features extracted are further sub-divided according to the areas located, i.e., spleen-stomach, liver-gall-left, liver-gall right, kidney, and heart-lung area. The purpose focuses on inducing significant tongue features (p<;0.05) to discriminate early-stage breast cancer patients from normal persons. The Mann-Whitney test shows that the amount of tongue fur (p = 0.024), maximum covering area of tongue fur (p = 0.009), thin tongue fur (p = 0.009), the average area of red dot (p = 0.049), the maximum area of red dot (p = 0.009), red dot in the spleen stomach area (p = 0.000), and red dot in the heart-lung area (p = 0.000) demonstrate significant differences. Next, the data collected are further classified into two groups. The training group consists of 57 early-stage breast cancer patients and 60 normal persons, while the testing group is composed of 10 early stage breast cancer patients and 10 normal persons. The logistic regression by utilizing these 7 tongue features with significant differences in Mann-Whitney test as factors is performed. In order to reduce the number of tongue features employed in prediction, we remove one of the 7 tongue features with lesser significant difference (p>0.05) and perform logistic regression twice. In the first time, we remove the maximum area of red dot (p = 0.266), and perform logistic regression. Among them, the amount of tongue fur (p = 0.000), the maximum covering area of tongue fur (p = 0.000), thin tongue fur (p = 0.008), the average area of red dot (p = 0.056), red dot in the spleen-stomach area (p = 0.005), red dot in the heart-lung area (p = 0.011) reveal independently significant meaning. In the second round, the average area of red dot (p = 0.056) is removed. The logistic regression shows that the amount of tongue fur (p = 0.001), the maximum covering area of tongue fur (p = 0.000), thin tongue fur (p = 0.007), red dot in the spleen-stomach area (p = 0.006), red dot in the heart-lung area (p = 0.003) reveal independently significant meaning. The tongue features of the testing group are employed in the aforementioned three models to test the power of significant tongue features identified in predicting early-stage breast cancer. An accuracy of 80%, 80% and 90% is reached on normal peoples by applying the 7, 6 and 5 significant tongue features obtained through Mann-Whitney test, respectively, while 60%, 60% and 50% is reached on the corresponding early-stage breast cancer patients.