Deep learning for Evaluation and Prediction of TecHnical Skills in robotic-assisted vaginal cuff closure study.
Saved in:
| Title: | Deep learning for Evaluation and Prediction of TecHnical Skills in robotic-assisted vaginal cuff closure study. |
|---|---|
| Authors: | Tesfai F; Institute for Women's Health, University College London, London, England; The Griffin Institute, Harrow, England., Xu J; Department of Medical Physics and Biomedical Engineering, University College London, London, England., Anastasiou D; Department of Medical Physics and Biomedical Engineering, University College London, London, England., He R; Department of Medical Physics and Biomedical Engineering, University College London, London, England., Boal M; The Griffin Institute, Harrow, England; Division of Surgery and Interventional Science, XXX, University College London, London, England., Aranan Y; Department of General Surgery, The Royal London Hospital, Barts Health NHS Trust, London, England., Lingam G; Institute for Women's Health, University College London, London, England., Shah D; University College London Medical School, London, England., Stoyanov D; Department of Medical Physics and Biomedical Engineering, University College London, London, England., Chandrasekaran D; University College London Hospitals NHS Foundation Trust., Mazomenos E; Department of Medical Physics and Biomedical Engineering, University College London, London, England., Francis N; The Griffin Institute, Harrow, England; Division of Surgery and Interventional Science, XXX, University College London, London, England. Electronic address: n.francis@griffininstitute.org.uk. |
| Source: | American journal of obstetrics and gynecology [Am J Obstet Gynecol] 2026 Aug; Vol. 235 (2), pp. 458-467. Date of Electronic Publication: 2026 Mar 19. |
| Publication Type: | Journal Article; Multicenter Study; Observational Study |
| Journal Info: | Publisher: Elsevier Country of Publication: United States NLM ID: 0370476 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-6868 (Electronic) Linking ISSN: 00029378 NLM ISO Abbreviation: Am J Obstet Gynecol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
Be the first to leave a comment!
