A study of the agreement between an automatic tongue diagnosis system and traditional Chinese medicine practitioners

2012 ◽  
Vol 4 ◽  
pp. 193
Author(s):  
Chiang John ◽  
Lo Lun-Chien ◽  
Cheng Tsung-Lin ◽  
Chen Wen-Jiuan ◽  
Chen Yung-Fu
2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Lun-chien Lo ◽  
Yung-Fu Chen ◽  
Wen-Jiuan Chen ◽  
Tsung-Lin Cheng ◽  
John Y. Chiang

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±0.06versus0.64±0.13) withP<0.001(Student’st-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.


Author(s):  
Lun-chien Lo ◽  
Yung-fu Chen ◽  
John Y. Chiang ◽  
Tsung-lin Cheng ◽  
Natsagdorj Damdinsuren

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Cui ◽  
Shizhong Liao ◽  
Hongwu Wang

Objective. To select significant Haar-like features extracted from tongue images for health identification.Materials and Methods. 1,322 tongue cases were included in this study. Health information and tongue images of each case were collected. Cases were classified into the following groups: group containing 148 cases diagnosed as health; group containing 332 cases diagnosed as ill based on health information, even though tongue image is normal; and group containing 842 cases diagnosed as ill. Haar-like features were extracted from tongue images. Then, we proposed a new boosting method in the ROC space for selecting significant features from the features extracted from these images.Results. A total of 27 features were obtained from groups A, B, and C. Seven features were selected from groups A and B, while 25 features were selected from groups A and C.Conclusions. The selected features in this study were mainly obtained from the root, top, and side areas of the tongue. This is consistent with the tongue partitions employed in traditional Chinese medicine. These results provide scientific evidence to TCM tongue diagnosis for health identification.


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