Tongue diagnosis indices for gastroesophageal reflux disease

Wu, Tzu-Chan; Lu, Cheng-Nan; Hu, Wen-Long; Wu, Keng‐Liang; Chiang, John Y.; Sheen, Jer-Ming; Hung, Yu‐Chiang

doi:10.1097/md.0000000000020471

Cited by 18 publications

(12 citation statements)

References 39 publications

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“…[44,45] The value of the TCTD diagnostic method is evident in diagnosing a variety of diseases, including breast cancer, gastrointestinal disorders, COVID-19, and diabetes. [17,[44][45][46][47] For instance, the proportion of greasy coatings was higher in patients with critical COVID-19 pneumonia compared patients with mild, moderate, and severe COVID-19 pneumonia. [44] The amount and thickness of tongue coatings in the spleen-stomach area are related to the severity of gastroesophageal reflux disease.…”

Section: Discussionmentioning

confidence: 99%

“…Tongue diagnosis is an indispensable part of TCM diagnosis and can reflect the severity and development of diseases. [44,45] The value of the TCTD diagnostic method is evident in diagnosing a variety of diseases, including breast cancer, gastrointestinal disorders, COVID-19, and diabetes. [17,[44][45][46][47] For instance, the proportion of greasy coatings was higher in patients with critical COVID-19 pneumonia compared patients with mild, moderate, and severe COVID-19 pneumonia.…”

Section: Discussionmentioning

confidence: 99%

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Tongue features of patients with granulomatous lobular mastitis

et al. 2022

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Traditional Chinese tongue diagnosis plays an irreplaceable role in disease diagnosis. This study aimed to describe the tongue characteristics of patients with granulomatous lobular mastitis (GLM). Forty GLM patients and 40 non-GLM controls were evaluated using the Traditional Chinese Medicine subjective clinical interpretation and a TDA-1 Tongue Diagnostic and Analysis system. The associations between the image features of the tongue body and coating and the profiling of immune-inflammatory parameters were analyzed. GLM patients were prone to a reddish tongue bodies with thick, white, and greasy coatings. Thick and greasy tongue coating features are risk factors for GLM. GLM patients had higher levels of white blood cells (WBC), platelets, C-reactive protein, interleukin-2, and transforming growth factor-β (TGF-β) than non-GLM controls (P < .05). Also, tongue coating contrast and entropy values were significantly correlated with WBC or TGF-β levels in GLM patients (r < −0.310 and P < .05). We demonstrated that the hot evil and phlegm-dampness constitutions are the main characteristics of GLM. This might provide a reference for GLM diagnosis.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Tongue features of patients with granulomatous lobular mastitis

et al. 2022

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“…According to the TCM tongue diagnosis theory, the normal thickness of tongue fur should be thin and uniform, while very thick or very thin (or absent) tongue fur may indicate some diseases or prediseases in the body [ 23 ]. Correspondingly, modern research has observed that gastroesophageal reflux disease and type 2 diabetes patients tend to have thick tongue fur [ 24 , 25 ], while primary dysmenorrhea patients tend to have less tongue fur [ 26 ]. From the perspective of tumor markers, our results also suggest that people with thick tongue fur or peeling or less tongue fur are more likely to have health issues.…”

Section: Discussionmentioning

confidence: 99%

A Nonlinear Association between Tongue Fur Thickness and Tumor Marker Abnormality: A Cross-Sectional Study

Zhu

Guo

Tang

et al. 2021

Evidence-Based Complementary and Alternative Medicine

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Background. Many associations between tongue fur and different physiological and biochemical indexes have been revealed. However, the relationship between tongue fur and tumor markers remains unexplored. Methods. We collected the medical examination reports of 1625 participants. Participants were residents of Chengdu, China, undergoing routine health checkups at the health management center of the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine between December 2018 and September 2020. The participants’ tongue fur thickness was measured using the DAOSH four-diagnostic instrument. Tumor marker levels, including t-PSA, AFP, CEA, CA125, and CA199, were measured in the clinical laboratory. Curve-fitting and multivariable logistic regression were used to analyze the association between tongue fur thickness and tumor marker abnormality. Results. Curve-fitting showed that the relationship between tongue fur thickness and abnormal tumor marker rate was nonlinear, similar to a U shape. As the tongue fur thickness value increased, the abnormal tumor marker probability initially decreased and then increased. Logistic regression showed that, in the crude model, compared with the thin tongue fur group, the odds ratios (ORs) and 95% confidence intervals (CIs) of the less or peeling tongue fur group and thick tongue fur group for tumor marker abnormality were 1.79 (1.02–3.17) and 1.70 (1.13–2.54), respectively. After adjusting gender, age, body mass index (BMI), smoking history, drinking history, tongue color, the form of the tongue, and fur color, the ORs and 95% CIs of the less or peeling tongue fur group and thick tongue fur group were 1.93 (1.04–3.57) and 1.82 (1.17–2.81), respectively. Conclusions. Excessive or very little tongue fur is associated with tumor marker abnormality. Further cross-sectional studies are needed to evaluate the clinical value of tongue fur for cancer diagnosis and screening.

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“…The human tongue is an essential organ of the body and can provide much information on human health status [1,2]. Tongue diagnosis is a simple and noninvasive technique for the syndrome differentiation and treatment in traditional Chinese medicine (TCM) [3][4][5][6][7]. Sublingual varices are a symbol of TCM judgments of blood stasis.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Technique for the Severity Classification of Sublingual Varices according to Traditional Chinese Medicine

Chiang

et al. 2022

Computational and Mathematical Methods in Medicine

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Tongue diagnosis, a noninvasive examination, is an essential step for syndrome differentiation and treatment in traditional Chinese medicine (TCM). Sublingual vein (SV) is examined to determine the presence of blood stasis and blood stasis syndrome. Many studies have shown that the degree of SV stasis positively correlates with disease severity. However, the diagnoses of SV examination are often subjective because they are influenced by factors such as physicians’ experience and color perception, resulting in different interpretations. Therefore, objective and scientific diagnostic approaches are required to determine the severity of sublingual varices. This study aims at developing a computer-assisted system based on machine learning (ML) techniques for diagnosing the severity of sublingual varicose veins. We conducted a comparative study of the performance of several supervised ML models, including the support vendor machine, K-neighbor, decision tree, linear regression, and Ridge classifier and their variants. The main task was to differentiate sublingual varices into mild and severe by using images of patients’ SVs. To improve diagnostic accuracy and to accelerate the training process, we proposed using two model reduction techniques, namely, the principal component analysis in conjunction with the slice inverse regression and the convolution neural network (CNN), to extract valuable features during the preprocessing of data. Our results showed that these two extraction methods can reduce the training time for the ML methods, and the Ridge-CNN method can achieve an accuracy rate as high as 87.5%, which is similar to that of experienced TCM physicians. This computer-aided tool can be used for reference clinical diagnosis. Furthermore, it can be employed by junior physicians to learn and to use in clinical settings.

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Tongue diagnosis indices for gastroesophageal reflux disease

Cited by 18 publications

References 39 publications

Tongue features of patients with granulomatous lobular mastitis

Tongue features of patients with granulomatous lobular mastitis

A Nonlinear Association between Tongue Fur Thickness and Tumor Marker Abnormality: A Cross-Sectional Study

Machine Learning-Based Technique for the Severity Classification of Sublingual Varices according to Traditional Chinese Medicine

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