Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark

Wagner, Martin; P. Müller‐Stich, Beat; Kisilenko, Anna; Tran, Duc; Heger, Patrick; Mündermann, Lars; M Lubotsky, David; Müller, Benjamin; Davitashvili, Tornike; Capek, Manuela; Reinke, Annika; Reid, Carissa; Yu, Tong; Vardazaryan, Armine; Innocent Nwoye, Chinedu; Padoy, Nicolas; Liu, Xinyang; Lee, Eung-Joo; Disch, Constantin; Meine, Hans; Xia, Tong; Jia, Fucang; Kondo, Satoshi; Reiter, Wolfgang; Jin, Yueming; Long, Yonghao; Jiang, Meirui; Dou, Qi; Heng, Pheng‐Ann; Twick, Isabell; Kirtac, Kadir; Hosgor, Enes; Lindström Bolmgren, Jon; Stenzel, Michael; von Siemens, Björn; Zhao, L.; Ge, Zhenxiao; Sun, Haiming; Xie, Di; Guo, Mengqi; Liu, Daochang; Kenngott, Hannes; Nickel, Felix; von Frankenberg, Moritz; Mathis-Ullrich, Franziska; Kopp‐Schneider, Annette; Maier‐Hein, Lena; Speidel, Stefanie; Bodenstedt, Sebastian

doi:10.1016/j.media.2023.102770

Public

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark

Published in Medical Image Analysis • Feb 21, 2023

Authors:

Martin Wagner

Beat P. Müller‐Stich

Anna Kisilenko

Abstract

PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the operation through context-sensitive warnings and semi-autonomous robotic assistance or improve training of surgeons via ...

Subject

Workflow

Computer science

Generalizability theory

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