Evidence map›Paper›PMID 41050187›Full record

ArticleMayo Clinic proceedings. Digital health2025

A Standardized Temporal Segmentation Framework and Annotation Resource Library in Robotic Surgery.

Busisiwe Mlambo, Mallory Shields, Simon Bach, Armin Bauer, Andrew Hung, Omar Yusef Kudsi, Felix Neis, John Lazar, Daniel Oh, Robert Perez and 14 more

Abstract read
In one paragraph

Article in Mayo Clinic proceedings. Digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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  5. Article
  6. Opportunities and obstacles in harnessing intraoperative data.Journal of abdominal wall surgery : JAWS · 2026
    Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Busisiwe MlamboAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Mallory ShieldsAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Simon BachDepartment of Surgery, Queen Elizabeth Hospital, Birmingham, United Kingdom.
Armin BauerResearch Institute for Women's Health, Department of Women's Health, University Hospital of Tübingen, Germany.
Andrew HungCedars-Sinai Medical Center, Los Angeles, CA.
Omar Yusef KudsiDepartment of Surgery, Good Samaritan Medical Center, Brockton, MA.
Felix NeisResearch Institute for Women's Health, Department of Women's Health, University Hospital of Tübingen, Germany.
John LazarDivision of Thoracic Surgery, Ascension Saint Thomas Hospital/University of Tennessee Health Science Center, Nashville, TN.
Daniel OhAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Robert PerezVirtua Memorial Hospital, Hainesport, NJ.
Seth RosenDepartment of Surgery, Emory University School of Medicine, Atlanta, GA.
Naeem SoomroDepartment of Urogynecology, Newcastle upon Tyne Hospitals Trust, Newcastle, United Kingdom.
Michael StanyDepartment of Gynecologic Surgery and Oncology, Ascension St. Thomas, Nashville, TN.
Mark TousignantMedical Safety and Innovation, Intuitive Surgical, Sunnyvale, CA.
Christian WagnerProstate Center Gronau, San Antonius Hospital, Gronau, Germany.
Ken WhalerAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Lilia PurvisAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Benjamin MuellerAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Sadia YousafAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Casey TroxlerAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Alfred SongAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Emily SummersAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Kiran BhattacharyyaAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.
Anthony JarcAdvanced Research and Analytics, Intuitive Surgical, Sunnyvale, CA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop and share the first clinical temporal annotation guide library for 10 robotic procedures accompanied with a standardized ontology framework for surgical video annotation. Patients and Methods: A standardized temporal annotation framework of surgical videos paired with consistent, procedure-specific annotation guides is critical to enable comparisons of surgical insights and facilitate large-scale insights for exceptional surgical practice. Existing ontologies and guidance not only provide foundational frameworks but also provide limited scalability in clinical settings. Building on these, we developed a temporal annotation framework with nested surgical phases, steps, tasks, and subtasks. Procedure-specific annotation resource guides consistent with this framework that define each surgical segment with formulaic start and stop parameters and surgical objectives were iteratively created across 7 years (January 1, 2018, to January 1, 2025) through global research collaborations with surgeon researchers and industry scientists. Results: We provide the first resource library of annotation guides for 10 common robotic procedures consistent with our proposed temporal annotation framework, enabling consistent annotations for clinicians and large-scale data comparisons with computer-readable examples. These have been used in over 13,000 annotated surgical cases globally, demonstrating reproducibility and broad applicability. Conclusion: This resource library and accompanying ontology framework provide critical structure for standardized temporal segmentation in robotic surgery. This framework has been applied globally in private studies examining surgical objective performance metrics, surgical education, workflow characterization, outcome prediction, algorithms for surgical activity recognition, and more. Adoption of these resources will unify clinical, academic, and industry efforts, ultimately catalyzing transformational advancements in surgical practice.

Identifiers

PMID41050187
PMCPMC12492233

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.