{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T19:49:27Z","timestamp":1791575367815,"version":"4.3.4"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,5,19]],"date-time":"2022-05-19T00:00:00Z","timestamp":1652918400000},"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. Cell Dev. Biol."],"abstract":"<jats:p><jats:bold>Background:<\/jats:bold>Anemia is the most common hematological disorder. The purpose of this study was to establish and validate a deep-learning model to predict Hgb concentrations and screen anemia using ultra-wide-field (UWF) fundus images.<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold>The study was conducted at Peking Union Medical College Hospital. Optos color images taken between January 2017 and June 2021 were screened for building the dataset. ASModel_UWF using UWF images was developed. Mean absolute error (MAE) and area under the receiver operating characteristics curve (AUC) were used to evaluate its performance. Saliency maps were generated to make the visual explanation of the model.<\/jats:p><jats:p><jats:bold>Results:<\/jats:bold>ASModel_UWF acquired the MAE of the prediction task of 0.83\u00a0g\/dl (95%CI: 0.81\u20130.85\u00a0g\/dl) and the AUC of the screening task of 0.93 (95%CI: 0.92\u20130.95). Compared with other screening approaches, it achieved the best performance of AUC and sensitivity when the test dataset size was larger than 1000. The model tended to focus on the area around the optic disc, retinal vessels, and some regions located at the peripheral area of the retina, which were undetected by non-UWF imaging.<\/jats:p><jats:p><jats:bold>Conclusion:<\/jats:bold>The deep-learning model ASModel_UWF could both predict Hgb concentration and screen anemia in a non-invasive and accurate way with high efficiency.<\/jats:p>","DOI":"10.3389\/fcell.2022.888268","type":"journal-article","created":{"date-parts":[[2022,5,19]],"date-time":"2022-05-19T06:04:37Z","timestamp":1652940277000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":50,"title":["Deep-Learning-Based Hemoglobin Concentration Prediction and Anemia Screening Using Ultra-Wide Field Fundus Images"],"prefix":"10.3389","volume":"10","author":[{"given":"Xinyu","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihui","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuanfeng","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guotong","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youxin","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,5,19]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e13969","DOI":"10.7759\/cureus.13969","article-title":"Bilateral Optic Atrophy in a Young Patient with Chronic Anaemia Secondary to End-Stage Renal Disease","volume":"13","author":"Ab Gani","year":"2021","journal-title":"Cureus"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1049","DOI":"10.1001\/archopht.1983.01040020051008","article-title":"Retinal Abnormalities Associated with Anemia","volume":"101","author":"Aisen","year":"1983","journal-title":"Arch. Ophthalmol."},{"key":"B3","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1177\/0300060514555562","article-title":"Peripapillary Retinal Nerve Fibre Layer Thickness in Women with Iron Deficiency Anaemia","volume":"43","author":"Akdogan","year":"2015","journal-title":"J. Int. Med. Res."},{"key":"B4","doi-asserted-by":"publisher","first-page":"340","DOI":"10.5281\/zenodo","article-title":"Development and Usability Assessment of a Connected Resistance Exercise Band Application for Strength-Monitoring","volume":"13","author":"Batsis","year":"2019","journal-title":"World Acad. Sci. Eng. Technol."},{"key":"B5","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1134\/s1054661819030027","article-title":"A Noninvasive Computerized Technique to Detect Anemia Using Images of Eye Conjunctiva","volume":"29","author":"Bauskar","year":"2019","journal-title":"Pattern Recognit. Image Anal."},{"key":"B6","doi-asserted-by":"publisher","first-page":"201","DOI":"10.4103\/0301-4738.181753","article-title":"Peripapillary Retinal Nerve Fiber Layer Thickness in Patients with Iron Deficiency Anemia","volume":"64","author":"Cikmazkara","year":"2016","journal-title":"Indian J. Ophthalmol."},{"key":"B7","doi-asserted-by":"publisher","first-page":"e0153286","DOI":"10.1371\/journal.pone.0153286","article-title":"Non-Invasive Detection of Anaemia Using Digital Photographs of the Conjunctiva","volume":"11","author":"Collings","year":"2016","journal-title":"PLoS One"},{"key":"B8","doi-asserted-by":"publisher","first-page":"1859","DOI":"10.1016\/S0140-6736(18)32335-3","article-title":"Global, Regional, and National Disability-Adjusted Life-Years (DALYs) for 359 Diseases and Injuries and Healthy Life Expectancy (HALE) for 195 Countries and Territories, 1990-2017: a Systematic Analysis for the Global Burden of Disease Study 2017","volume":"392","year":"2018","journal-title":"Lancet"},{"key":"B9","doi-asserted-by":"publisher","first-page":"3730","DOI":"10.1167\/iovs.10-6707","article-title":"Functional Characterization of Bestrophin-1 Missense Mutations Associated with Autosomal Recessive Bestrophinopathy","volume":"52","author":"Davidson","year":"2011","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"key":"B10","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1034\/j.1399-6576.2002.460809.x","article-title":"Accuracy of point-of-care-testing (POCT) for Determining Hemoglobin Concentrations","volume":"46","author":"Gehring","year":"2002","journal-title":"Acta Anaesthesiologica Scand."},{"key":"B11","doi-asserted-by":"publisher","first-page":"102478","DOI":"10.1016\/j.bspc.2021.102478","article-title":"Hemoglobin and Glucose Level Estimation from PPG Characteristics Features of Fingertip Video Using MGGP-Based Model","volume":"67","author":"Golap","year":"2021","journal-title":"Biomed. Signal Process. Control."},{"key":"B12","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1016\/j.jpeds.2021.11.013","article-title":"Ocular Manifestations in Patients with Fanconi Anemia: A Single Center Experience Including 106 Patients","volume":"242","author":"Graf","year":"2021","journal-title":"J. Pediatr."},{"key":"B13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12652-020-02618-3","article-title":"Ridge Regression Algorithm Based Non-invasive Anaemia Screening Using Conjunctiva Images","author":"Kasiviswanathan","year":"2020","journal-title":"J. Ambient Intelligence Humanized Comput."},{"key":"B14","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1016\/j.hoc.2015.11.002","article-title":"The Global Burden of Anemia","volume":"30","author":"Kassebaum","year":"2016","journal-title":"Hematology\/Oncology Clin. North America"},{"key":"B15","doi-asserted-by":"publisher","first-page":"777","DOI":"10.1136\/bjo.55.11.777","article-title":"Central Retinal Vein Occlusion Complicating Iron Deficiency Anaemia","volume":"55","author":"Kirkham","year":"1971","journal-title":"Br. J. Ophthalmol."},{"key":"B16","doi-asserted-by":"publisher","first-page":"2059","DOI":"10.1007\/s00417-020-04633-8","article-title":"Effects of Iron Deficiency Anemia on Peripapillary and Macular Vessel Density Determined Using Optical Coherence Tomography Angiography on Children","volume":"258","author":"Korkmaz","year":"2020","journal-title":"Graefes Arch. Clin. Exp. Ophthalmol."},{"key":"B17","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.1145\/3065386","article-title":"Imagenet Classification with Deep Convolutional Neural Networks","volume":"25","author":"Krizhevsky","year":"2012","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"B18","doi-asserted-by":"publisher","first-page":"e358","DOI":"10.1016\/s2589-7500(20)30108-4","article-title":"A Deep Learning Algorithm to Detect Anaemia with ECGs: a Retrospective, Multicentre Study","volume":"2","author":"Kwon","year":"2020","journal-title":"The Lancet Digital Health"},{"key":"B19","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1038\/s42003-019-0730-x","article-title":"Deep Learning for Detecting Retinal Detachment and Discerning Macular Status Using Ultra-widefield Fundus Images","volume":"3","author":"Li","year":"2020","journal-title":"Commun. Biol."},{"key":"B20","doi-asserted-by":"publisher","first-page":"4924","DOI":"10.1038\/s41467-018-07262-2","article-title":"Smartphone App for Non-invasive Detection of Anemia Using Only Patient-Sourced Photos","volume":"9","author":"Mannino","year":"2018","journal-title":"Nat. Commun."},{"key":"B21","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1007\/s00277-010-1144-5","article-title":"Anemia-still a Major Health Problem in many Parts of the World!","volume":"90","author":"Milman","year":"2011","journal-title":"Ann. Hematol."},{"key":"B22","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1038\/s41551-019-0487-z","article-title":"Detection of Anaemia from Retinal Fundus Images via Deep Learning","volume":"4","author":"Mitani","year":"2020","journal-title":"Nat. Biomed. Eng."},{"key":"B23","doi-asserted-by":"publisher","first-page":"9425","DOI":"10.1038\/s41598-017-09891-x","article-title":"Accuracy of Deep Learning, a Machine-Learning Technology, Using Ultra-wide-field Fundus Ophthalmoscopy for Detecting Rhegmatogenous Retinal Detachment","volume":"7","author":"Ohsugi","year":"2017","journal-title":"Sci. Rep."},{"key":"B24","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1016\/s0734-189x(87)80186-x","article-title":"Adaptive Histogram Equalization and its Variations","volume":"39","author":"Pizer","year":"1987","journal-title":"Comput. Vis. graphics, image Process."},{"key":"B25","doi-asserted-by":"crossref","DOI":"10.1109\/ICCV.2017.74","article-title":"Grad-cam: Visual Explanations from Deep Networks via Gradient-Based Localization","author":"Selvaraju","year":"2017"},{"key":"B26","doi-asserted-by":"publisher","first-page":"71","DOI":"10.4103\/tjo.tjo_27_18","article-title":"Megaloblastic Anemia and Bilateral Disc Edema: An enigma\u2026 Have We Figured it Out yet? Have We Figured it Out yet?","volume":"10","author":"Sethi","year":"2020","journal-title":"Taiwan J. Ophthalmol."},{"key":"B27","doi-asserted-by":"publisher","first-page":"5940","DOI":"10.1167\/iovs.15-18713","article-title":"Evaluation of Choroidal Thickness in Children with Iron Deficiency Anemia","volume":"57","author":"Simsek","year":"2016","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"key":"B28","article-title":"Striving for Simplicity: The All Convolutional Net","author":"Springenberg","year":"2014","journal-title":"arXiv"},{"key":"B29","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v31i1.11231","article-title":"Inception-v4, Inception-Resnet and the Impact of Residual Connections on Learning","author":"Szegedy","year":"2017"},{"key":"B30","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1038\/s41551-019-0504-2","article-title":"Detection of Anaemia from Retinal Images","volume":"4","author":"Tham","year":"2020","journal-title":"Nat. Biomed. Eng."},{"key":"B31","doi-asserted-by":"publisher","first-page":"217","DOI":"10.5301\/ejo.5000206","article-title":"Peripapillary Retinal Nerve Fiber Layer Thickness in Children with Iron Deficiency Anemia","volume":"23","author":"T\u00fcrkyilmaz","year":"2013","journal-title":"Eur. J. Ophthalmol."},{"key":"B32","doi-asserted-by":"publisher","first-page":"4387","DOI":"10.1172\/jci76666","article-title":"Disposable Platform Provides Visual and Color-Based point-of-care Anemia Self-Testing","volume":"124","author":"Tyburski","year":"2014","journal-title":"J. Clin. Invest."},{"key":"B33","doi-asserted-by":"publisher","first-page":"106773","DOI":"10.1016\/j.optlastec.2020.106773","article-title":"AneNet: A Lightweight Network for the Real-Time Anemia Screening from Retinal Vessel Optical Coherence Tomography Images","volume":"136","author":"Wei","year":"2021","journal-title":"Opt. Laser Technol."},{"key":"B34","doi-asserted-by":"publisher","first-page":"105761","DOI":"10.1016\/j.cmpb.2020.105761","article-title":"Deep Learning Can Generate Traditional Retinal Fundus Photographs Using Ultra-widefield Images via Generative Adversarial Networks","volume":"197","author":"Yoo","year":"2020","journal-title":"Comput. Methods Programs Biomed."},{"key":"B35","doi-asserted-by":"publisher","first-page":"2225","DOI":"10.1007\/s00417-021-05105-3","article-title":"Development of a Deep-Learning System for Detection of Lattice Degeneration, Retinal Breaks, and Retinal Detachment in Tessellated Eyes Using Ultra-wide-field Fundus Images: a Pilot Study","volume":"259","author":"Zhang","year":"2021","journal-title":"Graefes Arch. Clin. Exp. Ophthalmol."},{"key":"B36","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1167\/tvst.10.2.20","article-title":"Relationships between Retinal Vascular Characteristics and Renal Function in Patients with Type 2 Diabetes Mellitus","volume":"10","author":"Zhao","year":"2021","journal-title":"Trans. Vis. Sci. Tech."}],"container-title":["Frontiers in Cell and Developmental Biology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcell.2022.888268\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,5]],"date-time":"2023-02-05T14:41:31Z","timestamp":1675608091000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcell.2022.888268\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,19]]},"references-count":36,"alternative-id":["10.3389\/fcell.2022.888268"],"URL":"https:\/\/doi.org\/10.3389\/fcell.2022.888268","relation":{},"ISSN":["2296-634X"],"issn-type":[{"value":"2296-634X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,19]]},"article-number":"888268"}}