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

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.

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Publication Details

Journal
Mayo Clinic Proceedings Digital Health
Published
2025-08-22
DOI
https://doi.org/10.1016/j.mcpdig.2025.100257
Citations
1
Primary Topic
Surgical Simulation and Training
Type
article
Field-Weighted Citation Impact
2.01

Funders

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

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1 citations
Mayo Clinic Proceedings Digital Health
Surgical Simulation and Training
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article

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

Lilia Purvis, Seth A. Rosen, Emily Summers, Felix Neis, Michel Tousignant, Christian von Wagner, Robert X. Perez, Kiran Bhattacharyya, John F. Lazar, Simon P. Bach, Omar Yusef Kudsi, Alfred Song, Armin Bauer, Naeem Soomro, Andrew J. Hung, Mallory C. Shields, Anthony Jarc, Daniel Oh, Sadia Yousaf, Benjamin Mueller, K. A. Whaler, Busisiwe Mlambo, Michael Stany, Casey Troxler
article en
1 citations

Abstract

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.

Mayo Clinic Proceedings Digital HealthVol. 3(4)
University of Southern California (US), Saint Thomas West Hospital (US), Cedars-Sinai Medical Center (US), Brigham and Women's Hospital (US), Institute for Women's Policy Research (US), Saint Thomas Health (US), Emory University (US), Queen Elizabeth Hospital Birmingham (GB), Good Samaritan Medical Center (US), Intuitive Surgical (Switzerland) (CH), St.-Antonius-Hospital Gronau (DE), Virtua Memorial Hospital (US), Newcastle upon Tyne Hospital (GB), Women's Health Research Institute (CA), Intuitive Surgical (United States) (US), Intuit (United States) (US)
AstraZeneca, Intuitive Surgical
Openalex Percentile: Top 12%
Surgical Simulation and Training
2.01
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