{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T09:09:09Z","timestamp":1774602549089,"version":"3.50.1"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100006012","name":"Christian Doppler Forschungsgesellschaft","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006012","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Austrian Federal Ministry for Digital and Economic Affairs"},{"DOI":"10.13039\/100010132","name":"\u00d6sterreichische Nationalstiftung f\u00fcr Forschung, Technologie und Entwicklung","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010132","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1109\/jbhi.2020.3000136","type":"journal-article","created":{"date-parts":[[2020,6,4]],"date-time":"2020-06-04T19:53:13Z","timestamp":1591300393000},"page":"3456-3465","source":"Crossref","is-referenced-by-count":68,"title":["End-to-End Deep Learning Model for Predicting Treatment Requirements in Neovascular AMD From Longitudinal Retinal OCT Imaging"],"prefix":"10.1109","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1893-6854","authenticated-orcid":false,"given":"David","family":"Romo-Bucheli","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7788-7311","authenticated-orcid":false,"given":"Ursula Schmidt","family":"Erfurth","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9168-0894","authenticated-orcid":false,"given":"Hrvoje","family":"Bogunovic","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.18-25189"},{"key":"ref32","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"0","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.2307\/2531595"},{"key":"ref30","first-page":"8","article-title":"Image processing by linear interpolation and extrapolation","volume":"28","author":"haeberli","year":"1994","journal-title":"IRIS Universe Magazine"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2012.03.053"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa054481"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.preteyeres.2017.12.002"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"ref12","article-title":"Clinically applicable deep learning for diagnosis and referral in retinal disease","volume":"24","author":"fauw","year":"2018","journal-title":"Nature Medicine"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1364\/BOE.379150"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.18-25325"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-36745-x"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-27337-w"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2019.01.005"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.oret.2017.03.015"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2700213"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/0364-0213(90)90002-E"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.16-19963"},{"key":"ref27","first-page":"6391","article-title":"Visualizing the loss landscape of neural nets","author":"li","year":"0","journal-title":"Proc Neural Inf Process Syst Conf"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra0801537"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.16-19969"},{"key":"ref29","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"paszke","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajo.2017.09.027"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajo.2018.05.026"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2012.10.014"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2016.03.045"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.oret.2018.01.006"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.med.58.061705.145635"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.16-21053"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2017.10.031"},{"key":"ref21","first-page":"2894","article-title":"Comparison of RC and investigator determined retinal and subretinal fluid in the comparison of age-related macular degeneration treatment trials (CATT)","volume":"53","author":"toth","year":"2012","journal-title":"Investigative Ophthalmol Vis Sci"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2009.2016958"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10470-6_17"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1109\/TPAMI.2006.19","article-title":"Optimal surface segmentation in volumetric images-a graph-theoretic approach","volume":"28","author":"li","year":"2006","journal-title":"IEEE Trans Pattern Anal"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/9281055\/09108398.pdf?arnumber=9108398","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T17:20:00Z","timestamp":1651080000000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9108398\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12]]},"references-count":35,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2020.3000136","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12]]}}}