Research methods about data mining technology in the study medication Rule on Famous Veteran Teran Doctors of TCM

Wang, Yan; Liu, Yunfang; Yu, Lihui; Ma, Li; Cai, Xiaohong; Shen, Shaowu

doi:10.1109/bibm.2018.8621494

Cited by 4 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the rapid development of deep learning, researchers have tried to use its powerful feature extraction and semantic representative capabilities to im-prove the performance of tongue color classification in TCM [2], [3]. Hou et al [4] constructed a tongue image dataset and used a modified CaffeNet network to classify the tongue color.…”

Section: Tongue Color Classification In Tcm Based On Deep Learningmentioning

confidence: 99%

“…Next, it is necessary to define a confidence threshold to determine whether the label's prediction is credible. The threshold is the average probability of j self-confidence for each class , formulated as (2).…”

Section: Confident Learning In Teacher Networkmentioning

confidence: 99%

“…the confidence threshold is calculated by (2). Different methods are used to deal with noisy labels correspondingly.…”

Section: Confident Learning In Teacher Networkmentioning

confidence: 99%

See 2 more Smart Citations

Tongue Color Classification in TCM with Noisy Labels via Confident-Learning-Assisted Knowledge Distillation

Sun

et al. 2023

Chinese J. Elect.

View full text Add to dashboard Cite

Tongue color is an important tongue diagnostic index for traditional Chinese medicine (TCM). Due to the individual experience of TCM experts as well as ambiguous boundaries among the tongue color categories, there often exist noisy labels in annotated samples. Deep neural networks trained with the noisy labeled samples often have poor generalization capability because they easily overfit on noisy labels. A novel framework named confident-learning-assisted knowledge distillation (CLA-KD) is proposed for tongue color classification with noisy labels. In this framework, the teacher network plays two important roles. On the one hand, it performs confident learning to identify, cleanse and correct noisy labels. On the other hand, it learns the knowledge from the clean labels, which will then be transferred to the student network to guide its training. Moreover, we elaborately design a teacher network in an ensemble manner, named E-CA 2 -ResNet18, to solve the unreliability and instability problem resulted from the insufficient data samples. E-CA 2 -ResNet18 adopts ResNet18 as the backbone, and integrates channel attention (CA) mechanism and activate or not activation function together, which facilitates to yield a better performance. The experimental results on three self-established TCM tongue datasets demonstrate that, our proposed CLA-KD can obtain a superior classification accuracy and good robustness with a lower network model complexity, reaching 94.49%, 92.21%, 93.43% on the three tongue image datasets, respectively.

show abstract

Section: Tongue Color Classification In Tcm Based On Deep Learningmentioning

confidence: 99%

Section: Confident Learning In Teacher Networkmentioning

confidence: 99%

See 1 more Smart Citation

Tongue Color Classification in TCM with Noisy Labels via Confident-Learning-Assisted Knowledge Distillation

Sun

et al. 2023

Chinese J. Elect.

View full text Add to dashboard Cite

show abstract

“…Moreover, clinical observations and laboratory studies have indicated that TCM showed great potential for the treatment of BV, due to the capability of antibacteria, increasing biofilm permeability and drug susceptibility, enhancing body immunity, estrogen-liked effect, and so on (Duan et al, 2017). It is well-known that TCM treatment strategies are essentially based on the various combinations of different herbs in specific dosages (Wang, Liu, et al, 2018). At present, some TCM formulae, such as Yi Huang decoction (YHD), have been widely used for the clinical treatment of BV (Wang et al, 2020).…”

mentioning

confidence: 99%

Clinical research on traditional Chinese medicine treatment for bacterial vaginosis

Zhao

et al. 2021

Phytotherapy Research

View full text Add to dashboard Cite

Bacterial vaginosis (BV) is a common disease among women of reproductive age, with a serious impact on their daily life and health. At present, the most common treatment for BV is to take antibiotics, which results in good short‐term treatment effects, but poor long‐term effects. Traditional Chinese medicine (TCM) has been used to treat BV for over a millennium, with little risk of triggering drug resistance and adverse effects. Based on syndrome differentiation, there are three oral TCM treatment strategies for BV, including invigorating spleen, clearing dampness and heat, and nourishing kidney. The oral TCM prescriptions, such as Yi Huang decoction, Longdan Xiegan decoction, Zhibai Dihaung decoction, and so on are commonly used. Topical TCM treatment is also popular in China. According to the research results of pharmacological effects of active TCM ingredients, the most potential mechanisms of TCM for BV treatment are immune‐enhancement effects, antibacterial activity, and estrogen‐liked effects. Nonetheless, the multi‐constituent of herbs may result in possible disadvantages to BV treatment, and the pharmacological mechanisms of TCM need further study. Here, we provide an overview of TCM compounds and their preparations used for BV, based on the pathogenesis and the potential therapeutic mechanisms, therefore providing a reference for further studies.

show abstract

Research on treatment and medication rule of insomnia treated by TCM based on data mining

et al. 2019

2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

View full text Add to dashboard Cite

Research methods about data mining technology in the study medication Rule on Famous Veteran Teran Doctors of TCM

Cited by 4 publications

References 3 publications

Tongue Color Classification in TCM with Noisy Labels via Confident-Learning-Assisted Knowledge Distillation

Tongue Color Classification in TCM with Noisy Labels via Confident-Learning-Assisted Knowledge Distillation

Clinical research on traditional Chinese medicine treatment for bacterial vaginosis

Research on treatment and medication rule of insomnia treated by TCM based on data mining

Contact Info

Product

Resources

About