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.
Keywords: Automatic tongue diagnosis system; Breast cancer; Logistic regression; Mann–Whitney test.