Tongue feature dataset construction and real-time detection.

BACKGROUND: Tongue diagnosis in traditional Chinese medicine (TCM) provides clinically important, objective evidence from direct observation of specific features that assist with diagnosis. However, the current interpretation of tongue features requires a significant amount of manpower and time. TCM physicians may have different interpretations of features displayed by the same tongue. An automated interpretation system that interprets tongue features would expedite the interpretation process and yield more consistent results. MATERIALS AND METHODS: This study applied deep learning visualization to tongue diagnosis. After collecting tongue images and corresponding interpretation reports by TCM physicians in a single teaching hospital, various tongue features such as fissures, tooth marks, and different types of coatings were annotated manually with rectangles. These annotated data and images were used to train a deep learning object detection model. Upon completion of training, the position of each tongue feature was dynamically marked. RESULTS: A large high-quality manually annotated tongue feature dataset was constructed and analyzed. A detection model was trained with average precision (AP) 47.67%, 58.94%, 71.25% and 59.78% for fissures, tooth marks, thick and yellow coatings, respectively. At over 40 frames per second on a NVIDIA GeForce GTX 1060, the model was capable of detecting tongue features from any viewpoint in real time. CONCLUSIONS/SIGNIFICANCE: This study constructed a tongue feature dataset and trained a deep learning object detection model to locate tongue features in real time. The model provided interpretability and intuitiveness that are often lacking in general neural network models and implies good feasibility for clinical application.

Predictive Model for Oral Status in Elderly People in a Taiwanese Nursing Home Using a High-Protein Black Soybean Koji Food.

With increased age, the appetite, chewing, swallowing, and digestive ability gradually decrease. Previous studies have shown that poor oral health is associated with an inadequate intake of macro and micronutrients and malnutrition. Therefore, improving the diet of elderly people and promoting nutrient absorption will help to improve the quality of life for elderly people. However, few studies have predicted their oral ability based on different food textures and other factors. The purpose of this study was to explore the correlation between oral assessment and texture parameters of high-protein black soybean koji products in elderly people in a nursing home. We used cross-sectional study design for seventy-nine residents aged 65 years and older were recruited. Three different texture of cookies, including normal cookie hardness (1.4 × 105 N/m2), minced cookie hardness (4.4 × 104 N/m2), and pureed cookie hardness (1.4 × 104 N/m2) were provided to participants to test the oral status. An oral assessment scale was used by a dentist to evaluate the oral status of the elderly participants. Different cookie textures showed a significant positive correlation with pronunciation (r = 0.237, p < 0.05), face (r = 0.371, p < 0.01), tongue (r = 0.362, p < 0.01), pharynx (r = 0.256, p < 0.05), swallowing (r = 0.272, p < 0.05), breathing (r = 0.315, p < 0.01), and the total oral score (r = 0.339, p < 0.01). We also used the high-protein black soybean koji products combined with elderly people's comprehensions in a predictive model that had a moderately high correlation to predict the oral status in the elderly group (r = 0.612). We concluded that the high-protein black soybean koji product was associated with the oral ability of elderly people in a nursing home in Taiwan. Our findings indicated that elderly people could immediately understand the correct food texture.

Exploring the pivotal variables of tongue diagnosis between patients with acute ischemic stroke and health participants.

Background and aim: Stroke is a major cause of disability worldwide, and ischemic stroke is the most common type of stroke. The prevention and treatment of ischemic stroke remain a challenge worldwide. Traditional Chinese medicine (TCM) is often sought to provide an alternative therapy for the prevention and rehabilitation intervention of ischemic stroke in Taiwan. Therefore, this study explored the pivotal variables of tongue diagnosis among acute ischemic stroke and healthy participants in middle and older age. Experimental procedure: This was a cross-sectional and case-controlled study. Data were collected from 99 patients with acute ischemic stroke and 286 healthy participants who received tongue diagnoses at Changhua Christian Hospital (CCH) from September 1, 2014, to December 31, 2016. Tongue features were extracted using the automatic tongue diagnosis system. Nine tongue features, including tongue shape, tongue color, fur thickness, fur color, saliva, tongue fissures, ecchymoses, teeth marks, and red spots were analyzed. Results and conclusion: Objective image analysis techniques were used to identify significant differences in the many tongue features between patients with acute ischemic stroke and individuals without stroke. According to the logistic regression analysis, pale tongue color (OR:5.501, p = 0.001), bluish tongue color (OR:4.249, p = 0.014), ecchymoses (OR:1.058, p < 0.001), and tongue deviation angle (OR:1.218, p < 0.001) were associated with significantly increased odds ratios for acute ischemic stroke. The research revealed that tongue feature abnormalities were significantly related to the occurrence of ischemic stroke.

A Perspective on Tongue Diagnosis in Patients with Breast Cancer.

INTRODUCTION: Breast cancer (BC) is the most common cancer in women and patients with BC often undergo complex treatment. In Taiwan, nearly 80% of patients with BC seek traditional Chinese medicine (TCM) during adjuvant chemotherapy to relieve discomfort and side effects. This study investigated tongue features and pattern differentiation through noninvasive TCM tongue diagnosis in patients with BC. MATERIALS AND METHODS: This cross-sectional, case-controlled, retrospective observational study collected patient data through a chart review. The tongue features were extracted using the automatic tongue diagnosis system (ATDS). Nine tongue features, including tongue shape, tongue color, fur thickness, fur color, saliva, tongue fissures, ecchymoses, teeth marks, and red dots, were analyzed. Results and Discussion. Objective image analysis techniques were used to identify significant differences in the many tongue features between BC patients and non-BC individuals. A significantly larger proportion of patients with BC had a small tongue (p < 0.001), pale tongue (p < 0.001), thick fur (p < 0.001), yellow fur (p < 0.001), wet saliva (p < 0.001), thick tongue fur (p < 0.001), fissures (p=0.040), and ecchymoses in the heart-lung area (p=0.013). According to logistic regression, small tongue shape, pale tongue color, yellow fur color, wet saliva, and the amounts of fissures were associated with a significantly increased odds ratio for BC. CONCLUSIONS: This study showed significant differences in tongue features, such as small tongue shape, pale tongue color, thick fur, yellow fur color, wet saliva, fissure, and ecchymoses in the heart-lung area in patients with BC. These tongue features would imply yin deficiency, deficiencies of blood, stagnation of heat, and phlegm/blood stasis in TCM theory. There is a need to investigate effective and safe treatment to enhance the role of TCM in integrated medical care for patients with BC.

The tongue features associated with chronic kidney disease.

BACKGROUND: Traditional Chinese medicine (TCM) tongue diagnosis plays an important role in differentiation of symptoms because the tongue reflects the physiological and pathological condition of the body. The automatic tongue diagnosis system (ATDS), which noninvasively captures tongue images, can provide objective and reliable diagnostic information. Chronic kidney disease (CKD) currently is an important global public health problem and contributor to morbidity and mortality from non-communicable diseases. Thus, it is interesting to analyze and probe the relationship between tongue examination and CKD. METHODS: This protocol is a cross-sectional, case-controlled observational study investigating the usefulness of the ATDS in clinical practice by examining its efficacy as a diagnostic tool for CKD. Volunteers over 20 years old with and without CKD will be enrolled. Tongue images will be captured and the patients divided into 2 groups: CKD group and healthy group. Nine primary tongue features will be extracted and analyzed, including tongue shape, tongue color, tooth mark, tongue fissure, fur color, fur thickness, saliva, ecchymosis, and red dots. RESULT: The results of this study will systematically evaluate tongue manifestations of patients and examine its efficacy as an early detection and diagnosis of CKD. DISCUSSION: The aim of this protocol is to investigate discriminating tongue features to distinguish between CKD and normal people, and establish differentiating index to facilitate the noninvasive detection of CKD. TRIAL REGISTRIES: ClinicalTrials.gov; Identifier: NCT04708743.

Gender- and age-dependent tongue features in a community-based population.

This study, an important groundwork for clinical tongue diagnosis and future traditional Chinese medicine (TCM) research, tested the hypothesis that some tongue features vary significantly between different gender and age groups by utilizing an automatic tongue diagnosis system (ATDS).A cross-sectional study of 1487 participants from a community-based population was performed. Study subjects with ages ranging from 20 to 92 were categorized into 3 groups: <40, 40 to 64, and ≥65 years old, and the subjects were also stratified according to gender. Tongue images were collected at the end of each normal health examination routine to further derive the relevant tongue features of every participant by using the ATDS developed by our team. There were a total of nine tongue features that were identified: tongue shape, tongue color, fur thickness, fur color, saliva, tongue fissure, ecchymosis, teeth mark, and red dot. The corresponding tongue features, demography, and physical/laboratory examination data were compared between different gender and age groups.Our study showed that, compared to females, males had enlarged tongue shape, thicker fur, more fissures and fewer teeth marks (all P < .001), and also had more red tongue color (P = .019), normal saliva (P = .001), more red dots (P = .005) and yellower fur (P = .014). In females, increasing age was associated with more enlarged tongue shape, thicker fur, yellower fur, more saliva, fissures and fewer teeth marks (all P < .001), more ecchymoses (P = .009), and more red tongue color (P = .023). These associations of age with more fissures, fewer teeth marks, fewer red dots (P < .001), median tongue shape (P = .029), and wet saliva (P = .014) were also evident in males, but other relationships were not clearly evident.Even though most of the common tongue features derived from a community-based population are consistent with TCM theory, yet some significantly gender- and age-dependent tongue characteristics were identified. These disparities in tongue features associated with gender or age shall be prudently taken into consideration in clinical tongue diagnosis and future TCM research.

The tongue features associated with type 2 diabetes mellitus.

Diabetes mellitus (DM) is a public problem closely associated with numerous oral complications, such as coated tongue, xerostomia, salivary dysfunction, etc. Tongue diagnosis plays an important role in clinical prognosis and treatment of diabetes in the traditional Chinese medicine (TCM). This study investigated discriminating tongue features to distinguish between type 2 DM and non-DM individuals through non-invasive TCM tongue diagnosis.The tongue features for 199 patients with type 2 DM, and 372 non-DM individuals, serving as control, are extracted by the automatic tongue diagnosis system (ATDS). A total of 9 tongue features, namely, tongue shape, tongue color, fur thickness, fur color, saliva, tongue fissure, ecchymosis, teeth mark, and red dot. The demography, laboratory, physical examination, and tongue manifestation data between 2 groups were compared.Patients with type 2 DM possessed significantly larger covering area of yellow fur (58.5% vs 22.5%, P < .001), thick fur (50.8% vs 29.2%, P < .001), and bluish tongue (P < .001) than those of the control group. Also, a significantly higher portion (72.7% vs 55.2%, P < .05) of patients with long-term diabetics having yellow fur color than the short-term counterparts was observed.The high prevalence of thick fur, yellow fur color, and bluish tongue in patient with type 2 DM revealed that TCM tongue diagnosis can serve as a preliminary screening procedure in the early detection of type 2 DM 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 type 2 DM patients and non-DM individuals.