{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T16:57:34Z","timestamp":1777654654901,"version":"3.51.4"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"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":[[2022,9,27]]},"DOI":"10.1109\/bhi56158.2022.9926801","type":"proceedings-article","created":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T21:31:26Z","timestamp":1667597486000},"page":"01-04","source":"Crossref","is-referenced-by-count":6,"title":["Towards Graph Representation Learning Based Surgical Workflow Anticipation"],"prefix":"10.1109","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0228-6359","authenticated-orcid":false,"given":"Francis Xiatian","family":"Zhang","sequence":"first","affiliation":[{"name":"Durham University,Department of Computer Sciences,Durham,United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noura","family":"Al Moubayed","sequence":"additional","affiliation":[{"name":"Durham University,Department of Computer Sciences,Durham,United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hubert P. H.","family":"Shum","sequence":"additional","affiliation":[{"name":"Durham University,Department of Computer Sciences,Durham,United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/s41551-017-0132-7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59716-0_72"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2878055"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-019-01966-6"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32695-1_4"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561770"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87202-1_59"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87202-1_41"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00369"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59716-0_60"},{"key":"ref13","author":"Sarikaya","year":"2020","journal-title":"Towards generalizable surgical activity recognition using spatial temporal graph convolutional networks"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"ref15","article-title":"Inductive representation learning on large graphs","volume":"30","author":"Hamilton","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"ref17","author":"Jocher","year":"2022","journal-title":"ultralytics\/yolov 5: v6.1 - TensorRT, TensorFlow Edge TPU and OpenVINO Export and Inference"},{"key":"ref18","author":"Twinanda","year":"2016","journal-title":"Single-and multi-task architectures for surgical workflow challenge at m2cai 2016"},{"key":"ref19","author":"Kipf","year":"2017","journal-title":"Semi-supervised classification with graph convolutional networks. 2017"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00081"},{"key":"ref21","volume-title":"Experiment tracking with weights and biases","author":"Biewald","year":"2020"}],"event":{"name":"2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","location":"Ioannina, Greece","start":{"date-parts":[[2022,9,27]]},"end":{"date-parts":[[2022,9,30]]}},"container-title":["2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9926747\/9926739\/09926801.pdf?arnumber=9926801","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T07:35:44Z","timestamp":1709364944000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9926801\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,27]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/bhi56158.2022.9926801","relation":{},"subject":[],"published":{"date-parts":[[2022,9,27]]}}}