{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T06:04:34Z","timestamp":1790661874903,"version":"4.1.0"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Gastric cancer remains a major cause of cancer-related mortality, largely because many cases are diagnosed at an advanced stage. Upper gastrointestinal endoscopy with histopathological confirmation is the diagnostic gold standard, but its invasiveness, cost, and limited accessibility restrict population-level use. Artificial intelligence (AI)-based tongue-image analysis may provide an objective, low-cost, and non-invasive adjunct for pre-endoscopic risk stratification.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This systematic review was conducted according to PRISMA 2020 principles and was informed by diagnostic test accuracy and prediction-model reporting frameworks. PubMed\/MEDLINE, Scopus, Web of Science, and IEEE Xplore were searched from inception to 10 June 2026. Eligible studies were original investigations applying machine-learning or deep-learning methods to digital tongue images for gastric cancer, precancerous gastric lesions, or related gastrointestinal disorders and reporting at least one quantitative performance metric. Data were extracted on study design, sample size, target condition, reference standard, image-acquisition protocol, model architecture, validation strategy, diagnostic performance, calibration, interpretability, and risk of bias. A narrative synthesis was performed because of substantial heterogeneity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The search identified 139 records, of which 78 remained after duplicate removal. After title, abstract, and full-text screening, 9 studies published between 2018 and 2025 were included. The evidence covered gastric cancer, precancerous gastric lesions or high-risk gastric screening, and related gastrointestinal disorders. Models included logistic regression and XGBoost classifiers based on handcrafted features, convolutional neural networks, transformer-based architectures, segmentation-assisted pipelines, and multimodal models combining tongue images with clinical, questionnaire, biomarker, or microbiome data. Internally validated AUCs ranged from 0.61 to 0.99 across target conditions. External validation was reported in only three studies and generally showed performance degradation, particularly for precancerous gastric lesions. Calibration assessment was uncommon, and most studies did not report calibration curves, Brier scores, expected calibration error, or recalibration procedures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>AI-based tongue-image analysis is a promising but early-stage approach for non-invasive gastric disease screening. Current evidence supports its potential role as an adjunctive pre-endoscopic triage tool rather than a replacement for gastroscopy. Prospective external validation, standardized image acquisition, transparent model reporting, calibration assessment, and evaluation in diverse populations are required before clinical deployment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Systematic Review Registration<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link>https:\/\/www.crd.york.ac.uk\/PROSPERO\/view\/CRD420261444857<\/jats:ext-link>\n                      , PROSPERO CRD420261444857.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1931256","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T05:48:29Z","timestamp":1790660909000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence-based tongue image analysis for non-invasive screening of gastric cancer, precancerous lesions, and related gastrointestinal disorders: a systematic review"],"prefix":"10.3389","volume":"13","author":[{"given":"Rukai","family":"Wang","sequence":"first","affiliation":[{"name":"First School of Clinical medicine, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunlin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Neurology II, Shandong University of Traditional Chinese Medicine Affiliated Hospital","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hengyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"First School of Clinical medicine, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pingping","family":"Shao","sequence":"additional","affiliation":[{"name":"First School of Clinical medicine, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Gao","sequence":"additional","affiliation":[{"name":"First School of Clinical medicine, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenyue","family":"Zhang","sequence":"additional","affiliation":[{"name":"First School of Clinical medicine, Shandong University of Traditional Chinese Medicine","place":["Jinan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"229","DOI":"10.3322\/caac.21834","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J Clin"},{"key":"B2","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.semcancer.2023.04.009","article-title":"Application of artificial intelligence for improving early detection and prediction of therapeutic outcomes for gastric cancer in the era of precision oncology","volume":"93","author":"Wang","year":"2023","journal-title":"Semin Cancer Biol"},{"key":"B3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/6656053","article-title":"Development and application of artificial intelligence in auxiliary TCM diagnosis","volume":"2021","author":"Feng","year":"2021","journal-title":"Evid Based Complement Alternat Med"},{"key":"B4","doi-asserted-by":"publisher","first-page":"e9607","DOI":"10.1097\/MD.0000000000009607","article-title":"Tongue diagnosis indices for upper gastrointestinal disorders: protocol for a cross-sectional, case-controlled observational study","volume":"97","author":"Wu","year":"2018","journal-title":"Medicine (Baltimore)"},{"key":"B5","doi-asserted-by":"publisher","first-page":"102218","DOI":"10.1016\/j.eujim.2022.102218","article-title":"Tongue diagnosis models in Persian medicine: a Delphi study","volume":"58","author":"Farahi","year":"2023","journal-title":"Eur J Integr Med"},{"key":"B6","doi-asserted-by":"publisher","first-page":"20552076231191044","DOI":"10.1177\/20552076231191044","article-title":"A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation","volume":"9","author":"Liu","year":"2023","journal-title":"Digit Health"},{"key":"B7","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.imr.2018.03.001","article-title":"Advances in automated tongue diagnosis techniques","volume":"8","author":"Tania","year":"2019","journal-title":"Integr Med Res"},{"key":"B8","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.imr.2012.09.001","article-title":"Review on the current trends in tongue diagnosis systems","volume":"1","author":"Jung","year":"2012","journal-title":"Integr Med Res"},{"key":"B9","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1186\/s12880-024-01234-3","article-title":"Artificial intelligence in tongue diagnosis: classification of tongue lesions and normal tongue images using deep convolutional neural network","volume":"24","author":"Tiryaki","year":"2024","journal-title":"BMC Med Imaging"},{"key":"B10","doi-asserted-by":"publisher","first-page":"108074","DOI":"10.1016\/j.compbiomed.2024.108074","article-title":"A review of traditional Chinese medicine diagnosis using machine learning: inspection, auscultation-olfaction, inquiry, and palpation","volume":"170","author":"Tian","year":"2024","journal-title":"Comput Biol Med"},{"key":"B11","doi-asserted-by":"publisher","first-page":"101024","DOI":"10.1016\/j.imr.2024.101024","article-title":"Traditional, complementary, and integrative medicine and artificial intelligence: novel opportunities in healthcare","volume":"13","author":"Ng","year":"2024","journal-title":"Integr Med Res"},{"key":"B12","doi-asserted-by":"publisher","first-page":"161670","DOI":"10.1109\/ACCESS.2024.3486118","article-title":"Modernizing tongue diagnosis: AI integration with traditional Chinese medicine for precise health evaluation","volume":"12","author":"Jia","year":"2024","journal-title":"IEEE Access"},{"key":"B13","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1002\/tkm2.1255","article-title":"Assessing the efficacy of a tongue image analyzing system (TIAS) for the objective diagnosis of static blood: an observational, retrospective, single-center study of Japanese Kampo medicine","volume":"7","author":"Kainuma","year":"2020","journal-title":"Trad Kampo Med"},{"key":"B14","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/s40168-023-01730-8","article-title":"In-depth metaproteomics analysis of tongue coating for gastric cancer: a multicenter diagnostic research study","volume":"12","author":"Chen","year":"2024","journal-title":"Microbiome"},{"key":"B15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2022\/7210909","article-title":"Alterations of microorganisms in tongue coating of gastric precancerous lesion patients with a damp phlegm pattern","volume":"2022","author":"Xiao","year":"2022","journal-title":"BioMed Res Int"},{"key":"B16","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1007\/s13238-018-0596-6","article-title":"Tongue coating microbiome as a potential biomarker for gastritis including precancerous cascade","volume":"10","author":"Cui","year":"2019","journal-title":"Protein Cell"},{"key":"B17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2022\/7598427","article-title":"Microbial characteristics of common tongue coatings in patients with precancerous lesions of the upper gastrointestinal tract","volume":"2022","author":"Kang","year":"2022","journal-title":"J Healthc Eng"},{"key":"B18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2015\/173729","article-title":"Variations of tongue coating microbiota in patients with gastric cancer","volume":"2015","author":"Hu","year":"2015","journal-title":"Biomed Res Int"},{"key":"B19","doi-asserted-by":"publisher","first-page":"2964","DOI":"10.1007\/s10620-020-06637-0","article-title":"Tongue coating bacteria as a potential stable biomarker for gastric cancer independent of lifestyle","volume":"66","author":"Xu","year":"2021","journal-title":"Dig Dis Sci"},{"key":"B20","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1016\/j.jpba.2019.06.025","article-title":"Non-targeted metabolomics reveals diagnostic biomarker in the tongue coating of patients with chronic gastritis","volume":"174","author":"Mu","year":"2019","journal-title":"J Pharm Biomed Anal"},{"key":"B21","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1080\/17474124.2021.1850259","article-title":"Metabolome and microbiome alterations in tongue coating of gastric precancerous lesion patients","volume":"15","author":"Hao","year":"2021","journal-title":"Expert Rev Gastroenterol Hepatol"},{"key":"B22","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1186\/s12920-022-01209-9","article-title":"Species composition and overall diversity are significantly correlated between the tongue coating and gastric fluid microbiomes in gastritis patients","volume":"15","author":"Cui","year":"2022","journal-title":"BMC Med Genomics"},{"key":"B23","doi-asserted-by":"publisher","first-page":"e078378","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"Br Med J"},{"key":"B24","doi-asserted-by":"publisher","first-page":"e082505","DOI":"10.1136\/bmj-2024-082505","article-title":"PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods","volume":"388","author":"Moons","year":"2025","journal-title":"Br Med J"},{"key":"B25","doi-asserted-by":"publisher","first-page":"n2364","DOI":"10.1136\/bmj.n2364","article-title":"Effect of dietary sources of calcium and protein on hip fractures and falls in older adults in residential care: cluster randomised controlled trial","volume":"375","author":"Iuliano","year":"2021","journal-title":"Br Med J"},{"key":"B26","doi-asserted-by":"publisher","first-page":"746","DOI":"10.1007\/s11655-018-2840-6","article-title":"Application of computer-aided tongue inspection for preliminary screening of esophageal cancer","volume":"24","author":"Duan","year":"2018","journal-title":"Chin J Integr Med"},{"key":"B27","doi-asserted-by":"publisher","first-page":"271","DOI":"10.3390\/jpm13020271","article-title":"Construction of tongue image-based machine learning model for screening patients with gastric precancerous lesions","volume":"13","author":"Ma","year":"2023","journal-title":"J Pers Med"},{"key":"B28","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1186\/s13020-024-00963-5","article-title":"Development of an artificial intelligent model for pre-endoscopic screening of precancerous lesions in gastric cancer","volume":"19","author":"Wang","year":"2024","journal-title":"Chin Med"},{"key":"B29","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/s13020-025-01059-4","article-title":"Construction of machine learning-based models for screening the high-risk patients with gastric precancerous lesions","volume":"20","author":"Yu","year":"2025","journal-title":"Chin Med"},{"key":"B30","doi-asserted-by":"publisher","first-page":"101834","DOI":"10.1016\/j.eclinm.2023.101834","article-title":"Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study","volume":"57","author":"Yuan","year":"2023","journal-title":"eClinicalMed"},{"key":"B31","doi-asserted-by":"publisher","first-page":"53","DOI":"10.3390\/mi14010053","article-title":"A framework to predict gastric cancer based on tongue features and deep learning","volume":"14","author":"Zhu","year":"2022","journal-title":"Micromachines (Basel)"},{"key":"B32","doi-asserted-by":"publisher","first-page":"e20471","DOI":"10.1097\/MD.0000000000020471","article-title":"Tongue diagnosis indices for gastroesophageal reflux disease: a cross-sectional, case-controlled observational study","volume":"99","author":"Wu","year":"2020","journal-title":"Medicine (Baltimore)"},{"key":"B33","doi-asserted-by":"publisher","first-page":"e29269","DOI":"10.1016\/j.heliyon.2024.e29269","article-title":"Application of intelligent tongue image analysis in conjunction with microbiomes in the diagnosis of MAFLD","volume":"10","author":"Dai","year":"2024","journal-title":"Heliyon"},{"key":"B34","doi-asserted-by":"publisher","first-page":"106643","DOI":"10.1016\/j.bspc.2024.106643","article-title":"Intelligent tongue diagnosis model for gastrointestinal diseases based on tongue images","volume":"96","author":"Qiao","year":"2024","journal-title":"Biomed Signal Process Control"},{"key":"B35","doi-asserted-by":"publisher","first-page":"106126","DOI":"10.1016\/j.bspc.2024.106126","article-title":"A novel approach for early gastric cancer detection using a hybrid of AlexNet, extreme learning machine, and adjusted gorilla troops optimization","volume":"93","author":"Fan","year":"2024","journal-title":"Biomed Signal Process Control"},{"key":"B36","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/B978-0-443-45242-0.00007-4","article-title":"Chapter 1 - CARDIO-AI: compliance and artificial intelligence regulation for deep learning in electrocardiogram and cardiac signal interpretation","volume-title":"Deep Learning for Cardiac Signal Analysis in Robotic Applications","author":"Rajabi","year":"2026"}],"container-title":["Frontiers in Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2026.1931256\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T05:48:29Z","timestamp":1790660909000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2026.1931256\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,29]]},"references-count":36,"alternative-id":["10.3389\/fmed.2026.1931256"],"URL":"https:\/\/doi.org\/10.3389\/fmed.2026.1931256","relation":{},"ISSN":["2296-858X"],"issn-type":[{"value":"2296-858X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,29]]},"article-number":"1931256"}}