{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T03:21:00Z","timestamp":1762658460505,"version":"3.28.0"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"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":[],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1109\/isbi45749.2020.9098614","type":"proceedings-article","created":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T21:12:08Z","timestamp":1590181928000},"page":"1-5","source":"Crossref","is-referenced-by-count":3,"title":["Macular GCIPL Thickness Map Prediction via Time-Aware Convolutional LSTM"],"prefix":"10.1109","author":[{"given":"Zhiqi","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gadi","family":"Wollstein","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria","family":"de los Angeles Ramos-Cadena","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joel","family":"Schuman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroshi","family":"Ishikawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Learning to generate long-term future via hierarchical prediction","volume":"70","author":"villegas","year":"0","journal-title":"Proceedings of the 34th International Conference on Machine Learning"},{"key":"ref11","article-title":"Phased lstm: Accelerating recurrent network training for long or event-based sequences","author":"neil","year":"0","journal-title":"Advances in neural information processing systems"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/504"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3097997"},{"key":"ref14","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","author":"xingjian","year":"0","journal-title":"Advances in neural information processing systems"},{"journal-title":"Adam A method for stochastic optimization","year":"2014","author":"kingma","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0219126"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1001\/archopht.118.1.22","article-title":"The retinal nerve fiber layer thickness in ocular hypertensive, normal, and glaucomatous eyes with optical coherence tomography","volume":"118","author":"bowd","year":"2000","journal-title":"Arch Ophthalmol"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2018.03.052"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajo.2018.06.007"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1080\/02713683.2018.1439065","article-title":"Predicting the Integrated Visual Field with Wide-Scan Optical Coherence Tomography in Glaucoma Patients","volume":"43","author":"yoshida","year":"2018","journal-title":"Current Eye Research"},{"journal-title":"Speech Recognition with Deep Recurrent Neural Networks","year":"2013","author":"graves","key":"ref8"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1109\/TBME.2013.2295605","article-title":"Glaucoma progression detection using structural retinal nerve fiber layer measurements and functional visual field points","volume":"61","author":"yousefi","year":"2013","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophtha.2018.02.010"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1136\/bjo.2005.081224"},{"journal-title":"Neural machine translation by jointly learning to align and translate","year":"2014","author":"bahdanau","key":"ref9"}],"event":{"name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","start":{"date-parts":[[2020,4,3]]},"location":"Iowa City, IA, USA","end":{"date-parts":[[2020,4,7]]}},"container-title":["2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9091448\/9098313\/09098614.pdf?arnumber=9098614","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:58:14Z","timestamp":1656453494000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9098614\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/isbi45749.2020.9098614","relation":{},"subject":[],"published":{"date-parts":[[2020,4]]}}}