gms | German Medical Science

MAINZ//2011: 56. GMDS-Jahrestagung und 6. DGEpi-Jahrestagung

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V.
Deutsche Gesellschaft für Epidemiologie e. V.

26. - 29.09.2011 in Mainz

Modeling surgical processes: an ontological approach

Meeting Abstract

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  • Heinrich Herre - IMISE/Universität Leipzig, Leipzig
  • Dayana Neumuth - Universität Leipzig, Leipzig
  • Frank Loebe - Universität Leipzig, Leipzig
  • Thomas Neumuth - Universität Leipzig, Leipzig

Mainz//2011. 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi). Mainz, 26.-29.09.2011. Düsseldorf: German Medical Science GMS Publishing House; 2011. Doc11gmds421

doi: 10.3205/11gmds421, urn:nbn:de:0183-11gmds4210

Published: September 20, 2011

© 2011 Herre et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Introduction, motivation and background: The precise and formal specification of surgical interventions is a necessary requirement for many applications in surgery, including teaching and learning, quality assessment and evaluation, and computer-assisted surgery. Currently, surgical processes are modeled by using various distinct approaches, and this diversity lacks a commonly agreed-upon conceptual foundation and thus impedes the comparability, the interoperability, and the uniform interpretation of process data. We report on work in progress of an approach for modeling surgical processes, based on a uniform foundation, which was initiated in [1] and is planned as a long term project.

Methods: The method introduces four levels of description which are connected by ontological basic relations [1]. The natural language level is related to the user, being mainly surgeons and medical engineers; the ontological level deals with the analysis of domain knowledge and uses the method of ontological reduction [2]; the formal level provides for mathematical formalizations of domain knowledge dedicated to determinate purposes. Maintaining the link to the ontological level allows for interoperability and comparability of different models, making cross-modeling approaches possible and thus the gathering of knowledge from different sources and from different points of view. The implementation level is concerned with the realization of formalizations in languages with a practical orientation.

Results: The framework allows for a uniform representation of process models arising from different techniques. In [1], we analyzed a model for laparoscopic Nissen fundoplications, one for cerebral tumor surgery, a model for laparoscopic cholecystemies, and one model applicable to multiple surgical disciplines [3]. This uniform representation supports the comparability, measurability, interoperability, and communicability of findings, statistical interpretations, and data mining operations, as well as software applications.

Discussion and conclusion: The growing number of recent studies based on surgical workflows and time-action analyses shows the rising interest in this subject area. That interest can be accounted for by the multitude of possible applications, among them the evaluation of surgical assist systems or surgical skills, the design of technical support systems for the operating room, the conception of surgical knowledge bases and the generation of knowledge from them, the planning of interventions, requirements analyses, and so forth. For all of these applications, surgical process models could be more useful if they were designed according to a common basis. The formal framework and the embedding methodology presented here provide a coherent and rigorous contribution towards this end.


Neumuth D, Loebe F, Herre H, Neumuth T. Modeling surgical processes: A four-level translational approach. Artificial Intelligence in Medicine. 2011;51:147-161.
Herre H. General Formal Ontology: A foundational ontology for conceptual modeling. In: Theory and Application of Ontology: Computer Applications. Berlin: Springer; 2010.
Neumuth T, Jannin P, Strauss G, Meixensberger J, Burgert O. Validation of knowledge acquisition for surgical process models. Journal of the American Medical Informatics Association. 2009;16:72-80.