{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T17:10:13Z","timestamp":1782234613846,"version":"3.54.5"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1109\/jbhi.2021.3052916","type":"journal-article","created":{"date-parts":[[2021,5,10]],"date-time":"2021-05-10T17:10:30Z","timestamp":1620666630000},"page":"3709-3720","source":"Crossref","is-referenced-by-count":36,"title":["Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-Task Learning"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6687-7054","authenticated-orcid":false,"given":"Lie","family":"Ju","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6500-0445","authenticated-orcid":false,"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9794-3221","authenticated-orcid":false,"given":"Huimin","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dwarikanath","family":"Mahapatra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9171-6949","authenticated-orcid":false,"given":"Paul","family":"Bonnington","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5880-8673","authenticated-orcid":false,"given":"Zongyuan","family":"Ge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/09286580701396720"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.17216"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1136\/bjo.86.7.716"},{"issue":"1","key":"ref4","first-page":"2568","article-title":"National diabetes fact sheet: National estimates and general information on diabetes and prediabetes in the united states","volume":"201","year":"2011"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.diabres.2009.10.007"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajo.2007.06.025"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_61"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-010-9454-7"},{"key":"ref9","first-page":"181","article-title":"An Effective Approach to Detect Lesions in Color Retinal Images","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","volume":"2","author":"Wang"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1046\/j.1464-5491.2002.00613.x"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-007-9103-y"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajo.2009.02.031"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.17077\/omia.1032"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2016.07.014"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref16","article-title":"Earliest diabetic retinopathy classification using deep convolution neural networks. pdf","author":"Sankar","year":"2016"},{"key":"ref17","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref18","first-page":"647","article-title":"DeCaf: A deep convolutional activation feature for generic visual recognition","volume-title":"Proc. Int. Conf. Int. Conf. Mach. Learn.","author":"Donahue"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01216-8_12"},{"key":"ref20","first-page":"5260","article-title":"Multiple ocular diseases detection based on joint sparse multi-task learning","volume-title":"Conf. Proc. IEEE Eng. Med. Biol. Soc.","volume":"2015","author":"Chen"},{"key":"ref21","first-page":"127","article-title":"Multiple ocular diseases classification with graph regularized probabilistic multi-label learning","volume-title":"Proc. Asian Conf. Comput. Vis","author":"Chen"},{"key":"ref22","first-page":"228","volume":"68","author":"Haneda","year":"2010","journal-title":"Nihon Rinsho"},{"issue":"1","key":"ref23","article-title":"Teleophthalmology","author":"Li","year":"2017","journal-title":"Chinese J. Medic."},{"key":"ref24","first-page":"1321","article-title":"On calibration of modern neural networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn.-Volume 70","author":"Guo"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref26","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref31","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","author":"Zagoruyko","year":"2017","journal-title":"ICLR"},{"key":"ref32","first-page":"2888","article-title":"Moonshine: Distilling with cheap convolutions","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Crowley"},{"key":"ref33","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tarvainen"},{"key":"ref34","first-page":"1607","article-title":"Born again neural networks","volume-title":"Int. Conf. Machine Learn.","author":"Furlanello"},{"key":"ref35","article-title":"Label refinery: Improving imagenet classification through label progression","author":"Bagherinezhad","year":"2018"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.754"},{"key":"ref37","article-title":"Unifying distillation and privileged information","author":"Lopez-Paz","year":"2015"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01294"},{"key":"ref39","first-page":"1817","article-title":"A framework for learning predictive structures from multiple tasks and unlabeled data","volume":"6","author":"Ando","year":"2005","journal-title":"J. Mach. Learn. Res."},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1162\/153244304322765658"},{"key":"ref41","first-page":"615","article-title":"Learning multiple tasks with kernel methods","volume":"6","author":"Evgeniou","year":"2005","journal-title":"J. Mach. Learn. Res."},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1287\/mksc.1070.0291"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015426"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.1315241"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102479"},{"key":"ref46","first-page":"1585","article-title":"Learning multiple related tasks using latent independent component analysis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1613\/jair.731"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-45167-9_41"},{"key":"ref49","article-title":"Learning multiple tasks with deep relationship networks","author":"Long","year":"2015"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.126"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.433"},{"key":"ref52","article-title":"An overview of multi-task learning in deep neural networks","author":"Ruder","year":"2017"},{"issue":"2","key":"ref53","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Workshop Challenges Representation Learn. ICML","volume":"3","author":"Lee"},{"key":"ref54","article-title":"Healthcare Foundation. Diabetic Retinopathy Detection","author":"California"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref57","article-title":"Eye Disease","author":"Albert"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/9559879\/09328568.pdf?arnumber=9328568","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,24]],"date-time":"2024-01-24T01:49:09Z","timestamp":1706060949000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9328568\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10]]},"references-count":57,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2021.3052916","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10]]}}}