{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T21:59:18Z","timestamp":1790891958972,"version":"4.1.0"},"reference-count":48,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["aaojournal.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Ophthalmology"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.ophtha.2026.07.038","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T05:56:50Z","timestamp":1785995810000},"update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Image-Based Artificial Intelligence for Automated Diagnosis and Clinical Activity Grading in Thyroid Eye Disease"],"prefix":"10.1016","author":[{"given":"Rui","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junzhe","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guang-yu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ophtha.2026.07.038_bib1","doi-asserted-by":"crossref","DOI":"10.1530\/ETJ-25-0363","article-title":"What has changed in thyroid eye disease in the last five years (2020-2025)","volume":"15","author":"Salvi","year":"2026","journal-title":"Eur Thyroid J"},{"key":"10.1016\/j.ophtha.2026.07.038_bib2","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.1016\/j.eprac.2025.06.011","article-title":"Thyroid eye disease: management, advances, and future opportunities","volume":"31","author":"Fox","year":"2025","journal-title":"Endocr Pract"},{"key":"10.1016\/j.ophtha.2026.07.038_bib3","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1097\/IOP.0000000000003017","article-title":"Incidence of alemtuzumab-induced thyroid-associated orbitopathy: a systematic review and meta-analysis","volume":"42","author":"Tran","year":"2025","journal-title":"Ophthalmic Plast Reconstr Surg"},{"key":"10.1016\/j.ophtha.2026.07.038_bib4","article-title":"The therapeutic revolution in thyroid eye disease: from orbital radiotherapy to teprotumumab and AI","volume":"13","author":"Yuan","year":"2026","journal-title":"Front Med (Lausanne)"},{"key":"10.1016\/j.ophtha.2026.07.038_bib5","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/s40618-025-02688-0","article-title":"Bibliometrics in thyroid eye disease","volume":"49","author":"Hai","year":"2026","journal-title":"J Endocrinol Invest"},{"key":"10.1016\/j.ophtha.2026.07.038_bib6","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1080\/01676830.2025.2510587","article-title":"Deep learning model for differentiating thyroid eye disease and orbital myositis on computed tomography (CT) imaging","volume":"44","author":"Ha","year":"2025","journal-title":"Orbit"},{"key":"10.1016\/j.ophtha.2026.07.038_bib7","doi-asserted-by":"crossref","DOI":"10.3389\/fendo.2021.644200","article-title":"Association of other autoimmune diseases with thyroid eye disease","volume":"12","author":"Kelada","year":"2021","journal-title":"Front Endocrinol (Lausanne)"},{"key":"10.1016\/j.ophtha.2026.07.038_bib8","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1007\/s10792-024-02934-z","article-title":"Interrater reliability of photographic assessment of thyroid eye disease using the VISA classification","volume":"44","author":"Boynes","year":"2024","journal-title":"Int Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib9","doi-asserted-by":"crossref","DOI":"10.1136\/bmjophth-2025-002264","article-title":"AI-based assessment of Clinical Activity Score and detection of active thyroid eye disease using facial images: validation of Glandy CAS","volume":"10","author":"Shin","year":"2025","journal-title":"BMJ Open Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib10","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1097\/01.iop.0000235499.34867.85","article-title":"VISA classification for Graves orbitopathy","volume":"22","author":"Dolman","year":"2006","journal-title":"Ophthalmic Plast Reconstr Surg"},{"key":"10.1016\/j.ophtha.2026.07.038_bib11","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1136\/bjo.73.8.639","article-title":"Clinical criteria for the assessment of disease activity in Graves\u2019 ophthalmopathy: a novel approach","volume":"73","author":"Mourits","year":"1989","journal-title":"Br J Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib12","doi-asserted-by":"crossref","DOI":"10.1136\/bmjopen-2021-053173","article-title":"Novel observational study protocol to develop a prediction model that identifies patients with Graves\u2019 ophthalmopathy insensitive to intravenous glucocorticoids pulse therapy","volume":"11","author":"Wang","year":"2021","journal-title":"BMJ Open"},{"key":"10.1016\/j.ophtha.2026.07.038_bib13","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.1007\/s40618-024-02304-7","article-title":"Glucocorticoid-induced adrenal insufficiency after therapy with intravenous methylprednisolone in patients with moderate-to-severe and active Graves\u2019 orbitopathy: assessment with a low-dose corticotropin test","volume":"47","author":"Pelewicz","year":"2024","journal-title":"J Endocrinol Invest"},{"key":"10.1016\/j.ophtha.2026.07.038_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2025.112644","article-title":"Research progress and clinical utility of multi-parameter orbital MRI in thyroid-associated ophthalmopathy","volume":"195","author":"Gou","year":"2026","journal-title":"Eur J Radiol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib15","first-page":"469","article-title":"Diagnosis of Graves\u2019 orbitopathy: imaging methods, challenges, and new perspectives","volume":"76","author":"Sulima","year":"2025","journal-title":"Endokrynol Pol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib16","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.clindermatol.2023.12.019","article-title":"Application of artificial intelligence in oculoplastics","volume":"42","author":"Cai","year":"2024","journal-title":"Clin Dermatol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib17","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1080\/08820538.2022.2139625","article-title":"Artificial intelligence in ophthalmology \u2013 status quo and future perspectives","volume":"38","author":"Wawer Matos","year":"2023","journal-title":"Semin Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib18","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1186\/s12886-025-03988-y","article-title":"Comparative analysis of deep learning architectures for thyroid eye disease detection using facial photographs","volume":"25","author":"Aghajani","year":"2025","journal-title":"BMC Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib19","doi-asserted-by":"crossref","first-page":"5099","DOI":"10.21037\/qims-24-80","article-title":"Deep learning methods for diagnosis of Graves\u2019 ophthalmopathy using magnetic resonance imaging","volume":"14","author":"Ma","year":"2024","journal-title":"Quant Imaging Med Surg"},{"key":"10.1016\/j.ophtha.2026.07.038_bib20","doi-asserted-by":"crossref","DOI":"10.3389\/fendo.2023.1300196","article-title":"Application of artificial intelligence in the assessment of thyroid eye disease (TED) \u2013 a scoping review","volume":"14","author":"Chng","year":"2023","journal-title":"Front Endocrinol (Lausanne)"},{"key":"10.1016\/j.ophtha.2026.07.038_bib21","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.survophthal.2025.07.008","article-title":"Artificial intelligence in thyroid eye disease imaging: a systematic review","volume":"71","author":"Zhang","year":"2026","journal-title":"Surv Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib22","article-title":"Preferred reporting items for systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA): explanation, elaboration, and checklist","volume":"370","author":"Salameh","year":"2020","journal-title":"BMJ"},{"key":"10.1016\/j.ophtha.2026.07.038_bib23","doi-asserted-by":"crossref","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":"BMJ"},{"key":"10.1016\/j.ophtha.2026.07.038_bib24","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1016\/j.jclinepi.2014.01.006","article-title":"Applying Grading of Recommendations Assessment, Development and Evaluation (GRADE) to diagnostic tests was challenging but doable","volume":"67","author":"Gopalakrishna","year":"2014","journal-title":"J Clin Epidemiol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib25","doi-asserted-by":"crossref","first-page":"744","DOI":"10.1089\/thy.2023.0621","article-title":"A preliminary evaluation of the diagnostic performance of a smartphone-based machine learning-assisted system for evaluation of Clinical Activity Score in digital images of thyroid-associated orbitopathy","volume":"34","author":"Shin","year":"2024","journal-title":"Thyroid"},{"key":"10.1016\/j.ophtha.2026.07.038_bib26","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1177\/0272989X08319957","article-title":"Bivariate random effects meta-analysis of ROC curves","volume":"28","author":"Arends","year":"2008","journal-title":"Med Decis Making"},{"key":"10.1016\/j.ophtha.2026.07.038_bib27","doi-asserted-by":"crossref","first-page":"1539","DOI":"10.1002\/sim.1186","article-title":"Quantifying heterogeneity in a meta-analysis","volume":"21","author":"Higgins","year":"2002","journal-title":"Stat Med"},{"key":"10.1016\/j.ophtha.2026.07.038_bib28","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1056\/NEJM197507312930513","article-title":"Letter: nomogram for Bayes\u2019s theorem","volume":"293","author":"Fagan","year":"1975","journal-title":"N Engl J Med"},{"key":"10.1016\/j.ophtha.2026.07.038_bib29","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1001\/jama.1994.03510330081039","article-title":"Users\u2019 guides to the medical literature. III. How to use an article about a diagnostic test. B. What are the results and will they help me in caring for my patients? The Evidence-Based Medicine Working Group","volume":"271","author":"Jaeschke","year":"1994","journal-title":"JAMA"},{"key":"10.1016\/j.ophtha.2026.07.038_bib30","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1016\/j.jclinepi.2005.01.016","article-title":"The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed","volume":"58","author":"Deeks","year":"2005","journal-title":"J Clin Epidemiol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib31","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1007\/s11548-020-02281-1","article-title":"Artificial intelligence CT screening model for thyroid-associated ophthalmopathy and tests under clinical conditions","volume":"16","author":"Song","year":"2021","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"10.1016\/j.ophtha.2026.07.038_bib32","doi-asserted-by":"crossref","first-page":"3666","DOI":"10.1007\/s00259-023-06312-2","article-title":"Deep learning-based diagnosis of disease activity in patients with Graves\u2019 orbitopathy using orbital SPECT\/CT","volume":"50","author":"Yao","year":"2023","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"10.1016\/j.ophtha.2026.07.038_bib33","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1167\/iovs.65.5.6","article-title":"Deep-learning based automated segmentation and quantitative volumetric analysis of orbital muscle and fat for diagnosis of thyroid eye disease","volume":"65","author":"Alkhadrawi","year":"2024","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"10.1016\/j.ophtha.2026.07.038_bib34","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1186\/s12886-020-01783-5","article-title":"Detection of active and inactive phases of thyroid-associated ophthalmopathy using deep convolutional neural network","volume":"21","author":"Lin","year":"2021","journal-title":"BMC Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib35","article-title":"Diagnostic precision in thyroid-associated ophthalmopathy using multi-center radiomics with 99mTc-DTPA SPECT\/CT","volume":"14","author":"Liu","year":"2024","journal-title":"Sci Rep"},{"key":"10.1016\/j.ophtha.2026.07.038_bib36","doi-asserted-by":"crossref","DOI":"10.3389\/fendo.2024.1365350","article-title":"An ensemble deep learning diagnostic system for determining Clinical Activity Scores in thyroid-associated ophthalmopathy: integrating multi-view multimodal images from anterior segment slit-lamp photographs and facial images","volume":"15","author":"Yan","year":"2024","journal-title":"Front Endocrinol (Lausanne)"},{"key":"10.1016\/j.ophtha.2026.07.038_bib37","doi-asserted-by":"crossref","first-page":"1722","DOI":"10.1136\/bjo-2022-321833","article-title":"Ensemble neural network model for detecting thyroid eye disease using external photographs","volume":"107","author":"Karlin","year":"2023","journal-title":"Br J Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib38","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.ajo.2025.05.022","article-title":"Explainable deep learning system for automatic detection of thyroid eye disease using facial images","volume":"277","author":"Sui","year":"2025","journal-title":"Am J Ophthalmol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib39","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-25887-8","article-title":"Machine learning-assisted system using digital facial images to predict the clinical activity score in thyroid-associated orbitopathy","volume":"12","author":"Moon","year":"2022","journal-title":"Sci Rep"},{"key":"10.1016\/j.ophtha.2026.07.038_bib40","doi-asserted-by":"crossref","first-page":"2550","DOI":"10.1109\/JBHI.2025.3608153","article-title":"MediTEDNet: visual state space model for thyroid eye disease classification","volume":"30","author":"Han","year":"2025","journal-title":"IEEE J Biomed Health Inform"},{"key":"10.1016\/j.ophtha.2026.07.038_bib41","first-page":"11","article-title":"Multidimensional predictive model for assessing clinical activity in thyroid eye disease","volume":"12","author":"Li","year":"2025","journal-title":"Front Med (Lausanne)"},{"key":"10.1016\/j.ophtha.2026.07.038_bib42","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2025.110301","article-title":"Multimodal large language models as assistance for evaluation of thyroid-associated ophthalmopathy","volume":"192","author":"Kim","year":"2025","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.ophtha.2026.07.038_bib43","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2022.110295","article-title":"Multiparametric magnetic resonance imaging for differentiating active from inactive thyroid-associated ophthalmopathy: added value from magnetization transfer imaging","volume":"151","author":"Hu","year":"2022","journal-title":"Eur J Radiol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib44","article-title":"Neural network application for assessing thyroid-associated orbitopathy activity using orbital computed tomography","volume":"13","author":"Lee","year":"2023","journal-title":"Sci Rep"},{"key":"10.1016\/j.ophtha.2026.07.038_bib45","doi-asserted-by":"crossref","first-page":"e164","DOI":"10.1097\/SCS.0000000000009919","article-title":"Retinal photograph-based deep learning system for detection of thyroid-associated ophthalmopathy","volume":"35","author":"Jiang","year":"2024","journal-title":"J Craniofac Surg"},{"key":"10.1016\/j.ophtha.2026.07.038_bib46","doi-asserted-by":"crossref","first-page":"161","DOI":"10.3348\/kjr.2025.1101","article-title":"Quantitative chemical exchange saturation transfer MRI for diagnosing thyroid-associated ophthalmopathy activity: a prospective feasibility study","volume":"27","author":"Wang","year":"2026","journal-title":"Korean J Radiol"},{"key":"10.1016\/j.ophtha.2026.07.038_bib47","doi-asserted-by":"crossref","DOI":"10.1016\/j.xops.2025.100791","article-title":"Deep learning-driven exophthalmometry through facial photographs in thyroid eye disease","volume":"5","author":"Park","year":"2025","journal-title":"Ophthalmol Sci"},{"key":"10.1016\/j.ophtha.2026.07.038_bib48","doi-asserted-by":"crossref","DOI":"10.3389\/fcell.2022.1069248","article-title":"Orbital and eyelid diseases: the next breakthrough in artificial intelligence?","volume":"10","author":"Bao","year":"2022","journal-title":"Front Cell Dev Biol"}],"container-title":["Ophthalmology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0161642026005439?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0161642026005439?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T21:30:54Z","timestamp":1790890254000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0161642026005439"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":48,"alternative-id":["S0161642026005439"],"URL":"https:\/\/doi.org\/10.1016\/j.ophtha.2026.07.038","relation":{},"ISSN":["0161-6420"],"issn-type":[{"value":"0161-6420","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Image-Based Artificial Intelligence for Automated Diagnosis and Clinical Activity Grading in Thyroid Eye Disease","name":"articletitle","label":"Article Title"},{"value":"Ophthalmology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ophtha.2026.07.038","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 American Academy of Ophthalmology, Inc. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}