Employing Process Models for Surgical Training

Denes A. Nagy, Kristof Takacs, Imre J. Rudas, Tamas Haidegger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The exponential rise in minimally invasive procedures throughout the last three decades shifted the focus from individual manual skills to complex engineering solutions. To streamline the delivery of these novel techniques, Surgical Process Models (SPMs) have been under development. SPMs provide the basis for machine learning algorithms to frame the surgical procedure and anchor themselves into the workflow. Process recording is an essential tool to create an accurate representation of the SPM. Process recording, continued with human expert evaluation have been used to assess operator skills and compare interventional approaches. In this paper, we present a web-based surgical process recording tool which is evaluated in a surgical training scenario. Our aim is to involve the trainees in process recording, therefore actively exploring the generic process model of laparoscopic cholecystectomy. Along with training we also use the process records to identify the most accurately represented time points of process transitions, therefore providing target events for future monitoring systems.

Original languageEnglish
Title of host publicationSAMI 2020 - IEEE 18th World Symposium on Applied Machine Intelligence and Informatics, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages101-104
Number of pages4
ISBN (Electronic)9781728131498
DOIs
Publication statusPublished - Jan 2020
Event18th IEEE World Symposium on Applied Machine Intelligence and Informatics, SAMI 2020 - Herl�any, Slovakia
Duration: Jan 23 2020Jan 25 2020

Publication series

NameSAMI 2020 - IEEE 18th World Symposium on Applied Machine Intelligence and Informatics, Proceedings

Conference

Conference18th IEEE World Symposium on Applied Machine Intelligence and Informatics, SAMI 2020
CountrySlovakia
CityHerl�any
Period1/23/201/25/20

Keywords

  • Ontology
  • Surgical Data Science
  • Surgical Process Modeling
  • Surgical Workflow

ASJC Scopus subject areas

  • Information Systems and Management
  • Health Informatics
  • Education
  • Artificial Intelligence
  • Computer Science Applications
  • Computer Networks and Communications

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  • Cite this

    Nagy, D. A., Takacs, K., Rudas, I. J., & Haidegger, T. (2020). Employing Process Models for Surgical Training. In SAMI 2020 - IEEE 18th World Symposium on Applied Machine Intelligence and Informatics, Proceedings (pp. 101-104). [9108732] (SAMI 2020 - IEEE 18th World Symposium on Applied Machine Intelligence and Informatics, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SAMI48414.2020.9108732