{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T22:02:31Z","timestamp":1793311351417,"version":"4.5.0"},"reference-count":23,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T00:00:00Z","timestamp":1779926400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["bjui-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BJU International"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To construct a reliable robot\u2010assisted radical prostatectomy (RARP) surgical phase\u2010recognition model and sought to deploy the model within the SurgSmart platform (Chengdu Withai Innovations Technology Co., Ltd., Chengdu, China) to explore its feasibility and preliminary clinical utility in real surgical workflows, including its usability, interpretability, and potential value for surgical education and quality review.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 72 complete RARP procedure videos were collected, and divided into training, verification and test groups (7:1:2). We adopted Hiera (Meta Platforms, Inc., Menlo Park, CA, USA), a hierarchical vision transformer, as the backbone model for surgical phase recognition. Model performance was evaluated using precision, recall, F1\u2010score, and overall accuracy. The trained model was deployed on the SurgSmart platform and tested in two real world RARP procedures to evaluate its feasibility for intraoperative and postoperative use.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Temporal annotation quality was high, with a mean inter\u2010annotator Intersection over Union (IoU) score of 0.99 and a weighted IoU score of 0.97. Based on the finalised annotations, the trained Hiera model achieved a weighted F1\u2010score of 0.91, a macro F1\u2010score of 0.90, and an overall accuracy of 0.91 on the test set. Across the seven surgical phases, \u2018urethral anastomosis\u2019 and \u2018intrafascial dissection\u2019 reached F1\u2010scores of 0.96 and 0.92, and the remaining phases demonstrated F1\u2010scores within the 0.85\u20130.96 range. The confusion matrix demonstrated that most surgical phases were correctly classified, with a high concentration of samples along the diagonal cells, indicating strong alignment between predicted and ground\u2010truth labels. During real\u2010time deployment, the system processed live surgical video streams continuously and generated phase predictions throughout the operation without interruption. All outputs were produced without processing errors or interface interruptions, confirming stable operation in both real\u2010time and retrospective modes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Accurate surgical phase recognition might be achievable in RARP under a limited but high\u2010quality data setting, although further validation with larger and more diverse datasets is needed to confirm these findings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/bju.70324","type":"journal-article","created":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T14:39:41Z","timestamp":1779979181000},"page":"324-333","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Automated recognition of surgical phases in robot\u2010assisted radical prostatectomy using a Hiera\u2010based vision transformer"],"prefix":"10.1111","volume":"138","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1372-4596","authenticated-orcid":false,"given":"Liang","family":"Liu","sequence":"first","affiliation":[{"name":"Urology Department Chongqing University Central Hospital, Fourth People's Hospital of Chongqing, Chongqing Emergency Medical Center, Chongqing University  Chongqing China"},{"name":"Department of Urology, Urologic Surgery Center Xinqiao Hospital, Third Military Medical University (Army Medical University)  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian\u2010Feng","family":"Huang","sequence":"additional","affiliation":[{"name":"Urology Department Chongqing University Central Hospital, Fourth People's Hospital of Chongqing, Chongqing Emergency Medical Center, Chongqing University  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rong\u2010Hui","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Urology, Urologic Surgery Center Xinqiao Hospital, Third Military Medical University (Army Medical University)  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Yang","sequence":"additional","affiliation":[{"name":"Chengdu Withai Innovations Technology Company  Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing\u2010Song","family":"Wu","sequence":"additional","affiliation":[{"name":"Chengdu Withai Innovations Technology Company  Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dian","family":"Qin","sequence":"additional","affiliation":[{"name":"Chengdu Withai Innovations Technology Company  Chengdu 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