{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T01:08:02Z","timestamp":1790125682481,"version":"4.0.1"},"reference-count":44,"publisher":"Elsevier BV","issue":"2","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:00:00Z","timestamp":1775606400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013915","name":"EPSRC Centre for Doctoral Training in Medical Imaging","doi-asserted-by":"publisher","award":["EP\/Z534754\/1"],"award-info":[{"award-number":["EP\/Z534754\/1"]}],"id":[{"id":"10.13039\/501100013915","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000765","name":"University College London","doi-asserted-by":"publisher","award":["EP-R513143-1"],"award-info":[{"award-number":["EP-R513143-1"]}],"id":[{"id":"10.13039\/501100000765","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000765","name":"University College London","doi-asserted-by":"publisher","award":["EP-S021930-1"],"award-info":[{"award-number":["EP-S021930-1"]}],"id":[{"id":"10.13039\/501100000765","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000765","name":"University College London","doi-asserted-by":"publisher","award":["EP-T517793-1"],"award-info":[{"award-number":["EP-T517793-1"]}],"id":[{"id":"10.13039\/501100000765","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["ajog.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["American Journal of Obstetrics and Gynecology"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.ajog.2026.03.015","type":"journal-article","created":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T17:37:15Z","timestamp":1773941835000},"page":"458-467","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep learning for Evaluation and Prediction of TecHnical Skills in robotic-assisted vaginal cuff closure study"],"prefix":"10.1016","volume":"235","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4303-666X","authenticated-orcid":false,"given":"Freweini","family":"Tesfai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dimitrios","family":"Anastasiou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runlong","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Boal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yekaterina","family":"Aranan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gita","family":"Lingam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diya","family":"Shah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danail","family":"Stoyanov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dhivya","family":"Chandrasekaran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evangelos","family":"Mazomenos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8498-9175","authenticated-orcid":false,"given":"Nader","family":"Francis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ajog.2026.03.015_bib1","doi-asserted-by":"crossref","DOI":"10.1001\/jamanetworkopen.2019.18911","article-title":"Trends in the adoption of robotic surgery for common surgical procedures","volume":"3","author":"Sheetz","year":"2020","journal-title":"JAMA Netw Open"},{"key":"10.1016\/j.ajog.2026.03.015_bib2","doi-asserted-by":"crossref","first-page":"588.e1","DOI":"10.1016\/j.ajog.2016.06.005","article-title":"Robotic-assisted vs traditional laparoscopic surgery for endometrial cancer: a randomized controlled trial","volume":"215","author":"M\u00e4enp\u00e4\u00e4","year":"2016","journal-title":"Am J Obstet Gynecol"},{"issue":"Suppl1","key":"10.1016\/j.ajog.2026.03.015_bib3","doi-asserted-by":"crossref","first-page":"e522s","DOI":"10.6061\/clinics\/2017\/e522s","article-title":"Introduction of robotic surgery for endometrial cancer into a Brazilian cancer service: a randomized trial evaluating perioperative clinical outcomes and costs","volume":"73","author":"Silva","year":"2018","journal-title":"Clinics (Sao Paulo)"},{"key":"10.1016\/j.ajog.2026.03.015_bib4","doi-asserted-by":"crossref","first-page":"6672","DOI":"10.1007\/s00464-023-10275-8","article-title":"Laparoscopic versus robotic abdominal and pelvic surgery: a systematic review of randomised controlled trials","volume":"37","author":"Kawka","year":"2023","journal-title":"Surg Endosc"},{"key":"10.1016\/j.ajog.2026.03.015_bib5","series-title":"Top 10 health technology hazards executive brief 2020","year":"2020"},{"key":"10.1016\/j.ajog.2026.03.015_bib6","doi-asserted-by":"crossref","first-page":"1480","DOI":"10.1111\/aogs.14840","article-title":"Objective assessment tools in laparoscopic or robotic-assisted gynecological surgery: a systematic review","volume":"103","author":"Tesfai","year":"2024","journal-title":"Acta Obstet Gynecol Scand"},{"key":"10.1016\/j.ajog.2026.03.015_bib7","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1038\/s41746-022-00738-y","article-title":"Surgical gestures as a method to quantify surgical performance and predict patient outcomes","volume":"5","author":"Ma","year":"2022","journal-title":"NPJ Digit Med"},{"key":"10.1016\/j.ajog.2026.03.015_bib8","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-96336-5","article-title":"Automated assessment of simulated laparoscopic surgical skill performance using deep learning","volume":"15","author":"Power","year":"2025","journal-title":"Sci Rep"},{"key":"10.1016\/j.ajog.2026.03.015_bib9","doi-asserted-by":"crossref","first-page":"5018","DOI":"10.1007\/s00464-025-11903-1","article-title":"Surgical skill assessment using an AI-based surgical phase recognition model for laparoscopic cholecystectomy","volume":"39","author":"Yanagida","year":"2025","journal-title":"Surg Endosc"},{"key":"10.1016\/j.ajog.2026.03.015_bib10","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1109\/JPROC.2019.2946993","article-title":"CAI4CAI: the rise of contextual artificial intelligence in computer assisted interventions","volume":"108","author":"Vercauteren","year":"2020","journal-title":"Proc IEEE Inst Electr Electron Eng"},{"key":"10.1016\/j.ajog.2026.03.015_bib11","article-title":"Video analysis in minimally invasive surgery (VAMIS)","year":"2023","journal-title":"Health Research Authority"},{"key":"10.1016\/j.ajog.2026.03.015_bib13","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1111\/1471-0528.16399","article-title":"The influence of learning curve of robot-assisted laparoscopy on oncological outcomes in early-stage cervical cancer: an observational cohort study","volume":"128","author":"Baeten","year":"2021","journal-title":"BJOG"},{"key":"10.1016\/j.ajog.2026.03.015_bib14","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1097\/AOG.0b013e31827a029e","article-title":"The learning curve of robotic hysterectomy","volume":"121","author":"Woelk","year":"2013","journal-title":"Obstet Gynecol"},{"key":"10.1016\/j.ajog.2026.03.015_bib15","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1007\/s00464-019-07365-x","article-title":"Objective assessment of surgical operative performance by observational clinical human reliability analysis (OCHRA): a systematic review","volume":"34","author":"Tang","year":"2020","journal-title":"Surg Endosc"},{"key":"10.1016\/j.ajog.2026.03.015_bib16","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1001\/jamasurg.2020.1004","article-title":"Association of surgical skill assessment with clinical outcomes in cancer surgery","volume":"155","author":"Curtis","year":"2020","journal-title":"JAMA Surg"},{"key":"10.1016\/j.ajog.2026.03.015_bib17","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s10151-016-1444-4","article-title":"Application of objective clinical human reliability analysis (OCHRA) in assessment of technical performance in laparoscopic rectal cancer surgery","volume":"20","author":"Foster","year":"2016","journal-title":"Tech Coloproctol"},{"key":"10.1016\/j.ajog.2026.03.015_bib18","doi-asserted-by":"crossref","first-page":"3822","DOI":"10.1007\/s00464-018-6108-1","article-title":"EAES classification of intraoperative adverse events in laparoscopic surgery","volume":"32","author":"Francis","year":"2018","journal-title":"Surg Endosc"},{"key":"10.1016\/j.ajog.2026.03.015_bib19","doi-asserted-by":"crossref","DOI":"10.1002\/rcs.2375","article-title":"Analysis of executional and procedural errors in dry-lab robotic surgery experiments","volume":"18","author":"Hutchinson","year":"2022","journal-title":"Int J Med Robot"},{"key":"10.1016\/j.ajog.2026.03.015_bib20","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.juro.2011.09.032","article-title":"Global evaluative assessment of robotic skills: validation of a clinical assessment tool to measure robotic surgical skills","volume":"187","author":"Goh","year":"2012","journal-title":"J Urol"},{"key":"10.1016\/j.ajog.2026.03.015_bib21","first-page":"212","article-title":"Exploring pre-training across domains for few-shot surgical skill assessment","volume":"16191","author":"Anastasiou","year":"2025"},{"key":"10.1016\/j.ajog.2026.03.015_bib22","series-title":"CVPR","first-page":"14549","article-title":"VideoMAE v2: scaling video masked autoencoders with dual masking","author":"Wang","year":"2023"},{"key":"10.1016\/j.ajog.2026.03.015_bib23","series-title":"SAR-RARP50: segmentation of surgical instrumentation and action recognition on robot-assisted radical prostatectomy challenge","author":"Psychogyios","year":"2023"},{"key":"10.1016\/j.ajog.2026.03.015_bib24","series-title":"Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge","author":"Zia","year":"2023"},{"key":"10.1016\/j.ajog.2026.03.015_bib25","doi-asserted-by":"crossref","first-page":"1755","DOI":"10.1109\/LRA.2023.3242466","article-title":"Keep your eye on the best: contrastive regression transformer for skill assessment in robotic surgery","volume":"8","author":"Anastasiou","year":"2023","journal-title":"IEEE Robot Autom Lett"},{"key":"10.1016\/j.ajog.2026.03.015_bib26","series-title":"Multimodal action quality assessment","author":"Zeng","year":"2024"},{"key":"10.1016\/j.ajog.2026.03.015_bib27","series-title":"PyTorch implementation for \u2019personalizing federated instrument segmentation with visual trait priors in robotic surgery","year":"2025"},{"key":"10.1016\/j.ajog.2026.03.015_bib28","series-title":"Video Swin transformer","author":"Liu","year":"2022"},{"key":"10.1016\/j.ajog.2026.03.015_bib29","series-title":"Quo vadis, action recognition? A new model and the kinetics dataset","year":"2017"},{"key":"10.1016\/j.ajog.2026.03.015_bib30","series-title":"Proceedings of the international conference on medical image computing and computer-assisted intervention","first-page":"343","article-title":"Tecno: surgical phase recognition with multi-stage temporal convolutional networks","author":"Czempiel","year":"2020"},{"key":"10.1016\/j.ajog.2026.03.015_bib31","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"3575","article-title":"MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation","author":"Farha","year":"2019"},{"key":"10.1016\/j.ajog.2026.03.015_bib32","doi-asserted-by":"crossref","first-page":"6647","DOI":"10.1109\/TPAMI.2020.3021756","article-title":"Gall J MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation,\u201d","volume":"45","author":"Li","year":"2020","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.ajog.2026.03.015_bib33","series-title":"Runtime detection of executional errors in robot-assisted surgery in proceedings of the IEEE international conference on robotics and automation","author":"Li","year":"2022"},{"key":"10.1016\/j.ajog.2026.03.015_bib34","doi-asserted-by":"crossref","first-page":"11513","DOI":"10.1109\/LRA.2024.3495452","article-title":"Think step by step: chain-of-gesture prompting for error detection in robotic surgical videos","volume":"9","author":"Shao","year":"2024","journal-title":"IEEE Robot Autom Lett"},{"key":"10.1016\/j.ajog.2026.03.015_bib35","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1109\/LRA.2024.3505818","article-title":"SEDMamba: enhancing selective state space modelling with bottleneck mechanism and fine-to-coarse temporal fusion for efficient error detection in robot-assisted surgery","volume":"10","author":"Xu","year":"2025","journal-title":"IEEE Robot Autom Lett"},{"key":"10.1016\/j.ajog.2026.03.015_bib36","unstructured":"Oquab M, Darcet T, Moutakanni T, et al. DINOv2: learning robust visual features without supervision. Trans Mach Learn Res 2024.https:\/\/doi.org\/10.48550\/arXiv.2304.07193"},{"key":"10.1016\/j.ajog.2026.03.015_bib37","doi-asserted-by":"crossref","first-page":"2281","DOI":"10.1007\/s00464-022-09466-6","article-title":"Validity of video-based general and procedure-specific self-assessment tools for surgical trainees in laparoscopic cholecystectomy","volume":"37","author":"Balvardi","year":"2022","journal-title":"Surg Endosc"},{"key":"10.1016\/j.ajog.2026.03.015_bib38","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.yasu.2020.03.002","article-title":"Video assessment of surgeons and surgery","volume":"54","author":"Bilgi\u00e7","year":"2020","journal-title":"Adv Surg"},{"key":"10.1016\/j.ajog.2026.03.015_bib39","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1016\/j.jsurg.2019.05.013","article-title":"Video-based assessment in surgical education: a scoping review","volume":"76","author":"McQueen","year":"2019","journal-title":"J Surg Educ"},{"key":"10.1016\/j.ajog.2026.03.015_bib40","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.amjsurg.2020.06.027","article-title":"The what? How? And Who? Of video based assessment","volume":"221","author":"Pugh","year":"2020","journal-title":"Am J Surg"},{"key":"10.1016\/j.ajog.2026.03.015_bib41","doi-asserted-by":"crossref","first-page":"7328","DOI":"10.3390\/s22197328","article-title":"Multi-modal deep learning for assessing surgeon technical skill","volume":"22","author":"Kasa","year":"2022","journal-title":"Sensors (Basel)"},{"key":"10.1016\/j.ajog.2026.03.015_bib42","doi-asserted-by":"crossref","DOI":"10.1093\/bjs\/znad331","article-title":"Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review","volume":"111","author":"Boal","year":"2024","journal-title":"Br J Surg"},{"key":"10.1016\/j.ajog.2026.03.015_bib43","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1503\/cjs.032909","article-title":"Value of an objective assessment tool in the operating room","volume":"54","author":"Hiemstra","year":"2011","journal-title":"Can J Surg"},{"key":"10.1016\/j.ajog.2026.03.015_bib44","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1097\/SLA.0000000000003452","article-title":"Clinical evaluation of intraoperative near misses in laparoscopic rectal cancer surgery","volume":"273","author":"Curtis","year":"2021","journal-title":"Ann Surg"},{"key":"10.1016\/j.ajog.2026.03.015_bib45","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-16923-8","article-title":"Limited generalizability of single deep neural network for surgical instrument segmentation in different surgical environments","volume":"12","author":"Kitaguchi","year":"2022","journal-title":"Sci Rep"}],"container-title":["American Journal of Obstetrics and Gynecology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0002937826001651?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0002937826001651?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:36:43Z","timestamp":1790123803000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0002937826001651"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":44,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["S0002937826001651"],"URL":"https:\/\/doi.org\/10.1016\/j.ajog.2026.03.015","relation":{},"ISSN":["0002-9378"],"issn-type":[{"value":"0002-9378","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep learning for Evaluation and Prediction of TecHnical Skills in robotic-assisted vaginal cuff closure study","name":"articletitle","label":"Article Title"},{"value":"American Journal of Obstetrics and Gynecology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ajog.2026.03.015","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}