ArticleJournal of personalized medicine2023
Construction of Tongue Image-Based Machine Learning Model for Screening Patients with Gastric Precancerous Lesions.
Article in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 27 citations in OpenAlex.
- Development and validation of an interpretable machine learning model for non-invasive screening of precancerous gastric lesions using symptom and lifestyle data: a multicentre cohort study.EClinicalMedicine · 2026Article
- Traditional Chinese Medicine Modernization in Diagnosis and Treatment: Utilizing Artificial Intelligence and Nanotechnology.MedComm · 2026Review
- Clinical usefulness of objective tongue image devices monitoring in temporal tongue color: a demonstration of successively treated cases with traditional medicines.Frontiers in medicine · 2026Article
- Endoscopic and histopathological phenotypes of early gastric neoplasia: toward an integrative host-response framework.Frontiers in oncology · 2026Review
- Computerized tongue image analysis for non-invasive disease screening: a review.Chinese medicine · 2025Review
- Article
- Machine learning-assisted tongue image analysis for the diagnosis of Hashimoto's thyroiditis.Frontiers in medicine · 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
- Development and validation of a nomogram for obesity and related factors to detect gastric precancerous lesions in the Chinese population: a retrospective cohort study.Frontiers in oncology · 2024Article
- Feasibility of tongue image detection for coronary artery disease: based on deep learning.Frontiers in cardiovascular medicine · 2024Article
- Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine.Briefings in bioinformatics · 2023Review
- Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods.Cancer biology & medicine · 2023Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Screening patients with precancerous lesions of gastric cancer (PLGC) is important for gastric cancer prevention. The accuracy and convenience of PLGC screening could be improved with the use of machine learning methodologies to uncover and integrate valuable characteristics of noninvasive medical images related to PLGC. In this study, we therefore focused on tongue images and for the first time constructed a tongue image-based PLGC screening deep learning model (AITongue). The AITongue model uncovered potential associations between tongue image characteristics and PLGC, and integrated canonical risk factors, including age, sex, and Hp infection. Five-fold cross validation analysis on an independent cohort of 1995 patients revealed the AITongue model could screen PLGC individuals with an AUC of 0.75, 10.3% higher than that of the model with only including canonical risk factors. Of note, we investigated the value of the AITongue model in predicting PLGC risk by establishing a prospective PLGC follow-up cohort, reaching an AUC of 0.71. In addition, we developed a smartphone-based app screening system to enhance the application convenience of the AITongue model in the natural population from high-risk areas of gastric cancer in China. Collectively, our study has demonstrated the value of tongue image characteristics in PLGC screening and risk prediction.
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