ArticleMicromachines2022
A Framework to Predict Gastric Cancer Based on Tongue Features and Deep Learning.
Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Exploring traditional Chinese medicine tongue diagnosis in potential cancer identification: A scoping review.Integrative medicine research · 2026Review
- The association between tongue features and tongue coating microbiota and gastrointestinal cancer: a systematic review and meta-analysis.Journal of oral microbiology · 2026Review
- Objective pulse wave amplitude as a potential systemic correlate in childhood myopia: a digital TCM-based study.Frontiers in medicine · 2026Article
- Computerized tongue image analysis for non-invasive disease screening: a review.Chinese medicine · 2025Review
- A Deep Regression Model for Tongue Image Color Correction Based on CNN.Journal of imaging · 2025Article
- WHFDL: an explainable method based on World Hyper-heuristic and Fuzzy Deep Learning approaches for gastric cancer detection using metabolomics data.BioData mining · 2025Article
- Development of an artificial intelligent model for pre-endoscopic screening of precancerous lesions in gastric cancer.Chinese medicine · 2024Article
- Artificial intelligence in tongue diagnosis: classification of tongue lesions and normal tongue images using deep convolutional neural network.BMC medical imaging · 2024Article
- Artificial intelligence: clinical applications and future advancement in gastrointestinal cancers.Frontiers in artificial intelligence · 2024Review
- Effects of Sitting and Supine Positions on Tongue Color as Measured by Tongue Image Analyzing System and Its Relation to Biometric Information.Evidence-based complementary and alternative medicine : eCAM · 2024Article
- Editorial for the Special Issue on Flexible and Wearable Sensors.Micromachines · 2023Article
- Construction of Tongue Image-Based Machine Learning Model for Screening Patients with Gastric Precancerous Lesions.Journal of personalized medicine · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
Gastric cancer has become a global health issue, severely disrupting daily life. Early detection in gastric cancer patients and immediate treatment contribute significantly to the protection of human health. However, routine gastric cancer examinations carry the risk of complications and are time-consuming. We proposed a framework to predict gastric cancer non-invasively and conveniently. A total of 703 tongue images were acquired using a bespoke tongue image capture instrument, then a dataset containing subjects with and without gastric cancer was created. As the images acquired by this instrument contain non-tongue areas, the Deeplabv3+ network was applied for tongue segmentation to reduce the interference in feature extraction. Nine tongue features were extracted, relationships between tongue features and gastric cancer were explored by using statistical methods and deep learning, finally a prediction framework for gastric cancer was designed. The experimental results showed that the proposed framework had a strong detection ability, with an accuracy of 93.6%. The gastric cancer prediction framework created by combining statistical methods and deep learning proposes a scheme for exploring the relationships between gastric cancer and tongue features. This framework contributes to the effective early diagnosis of patients with gastric cancer.
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