Literature DB >> 25752728

Multi-perspective workflow modeling for online surgical situation models.

Stefan Franke1, Jürgen Meixensberger2, Thomas Neumuth3.   

Abstract

INTRODUCTION: Surgical workflow management is expected to enable situation-aware adaptation and intelligent systems behavior in an integrated operating room (OR). The overall aim is to unburden the surgeon and OR staff from both manual maintenance and information seeking tasks. A major step toward intelligent systems behavior is a stable classification of the surgical situation from multiple perspectives based on performed low-level tasks.
MATERIAL AND METHODS: The present work proposes a method for the classification of surgical situations based on multi-perspective workflow modeling. A model network that interconnects different types of surgical process models is described. Various aspects of a surgical situation description were considered: low-level tasks, high-level tasks, patient status, and the use of medical devices. A study with sixty neurosurgical interventions was conducted to evaluate the performance of our approach and its robustness against incomplete workflow recognition input.
RESULTS: A correct classification rate of over 90% was measured for high-level tasks and patient status. The device usage models for navigation and neurophysiology classified over 95% of the situations correctly, whereas the ultrasound usage was more difficult to predict. Overall, the classification rate decreased with an increasing level of input distortion. DISCUSSION: Autonomous adaptation of medical devices and intelligent systems behavior do not currently depend solely on low-level tasks. Instead, they require a more general type of understanding of the surgical condition. The integration of various surgical process models in a network provided a comprehensive representation of the interventions and allowed for the generation of extensive situation descriptions.
CONCLUSION: Multi-perspective surgical workflow modeling and online situation models will be a significant pre-requisite for reliable and intelligent systems behavior. Hence, they will contribute to a cooperative OR environment.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Machine learning; Surgical workflow; Workflow modeling

Mesh:

Year:  2015        PMID: 25752728     DOI: 10.1016/j.jbi.2015.02.005

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  6 in total

Review 1.  A survey of context recognition in surgery.

Authors:  Igor Pernek; Alois Ferscha
Journal:  Med Biol Eng Comput       Date:  2017-07-10       Impact factor: 2.602

2.  Online time and resource management based on surgical workflow time series analysis.

Authors:  M Maktabi; T Neumuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-08-29       Impact factor: 2.924

3.  The intelligent OR: design and validation of a context-aware surgical working environment.

Authors:  Stefan Franke; Max Rockstroh; Mathias Hofer; Thomas Neumuth
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-05-24       Impact factor: 2.924

Review 4.  Surgical process modeling.

Authors:  Thomas Neumuth
Journal:  Innov Surg Sci       Date:  2017-05-20

Review 5.  Paradigm shift: cognitive surgery.

Authors:  Hannes G Kenngott; Martin Apitz; Martin Wagner; Anas A Preukschas; Stefanie Speidel; Beat Peter Müller-Stich
Journal:  Innov Surg Sci       Date:  2017-06-06

6.  Role of Intelligent Management Systems in Surgical Punctuality and Quality of Care.

Authors:  Gendi Li; Shenhui Huang
Journal:  Comput Intell Neurosci       Date:  2022-10-11
  6 in total

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