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Toward cognitive pipelines of medical assistance algorithms

  • Patrick PhilippEmail author
  • Maria Maleshkova
  • Darko Katic
  • Christian Weber
  • Michael Götz
  • Achim Rettinger
  • Stefanie Speidel
  • Benedikt Kämpgen
  • Marco Nolden
  • Anna-Laura Wekerle
  • Rüdiger Dillmann
  • Hannes Kenngott
  • Beat Müller
  • Rudi Studer
Original Article

Abstract

Purpose

Assistance algorithms for medical tasks have great potential to support physicians with their daily work. However, medicine is also one of the most demanding domains for computer-based support systems, since medical assistance tasks are complex and the practical experience of the physician is crucial. Recent developments in the area of cognitive computing appear to be well suited to tackle medicine as an application domain.

Methods

We propose a system based on the idea of cognitive computing and consisting of auto-configurable medical assistance algorithms and their self-adapting combination. The system enables automatic execution of new algorithms, given they are made available as Medical Cognitive Apps and are registered in a central semantic repository. Learning components can be added to the system to optimize the results in the cases when numerous Medical Cognitive Apps are available for the same task. Our prototypical implementation is applied to the areas of surgical phase recognition based on sensor data and image progressing for tumor progression mappings.

Results

Our results suggest that such assistance algorithms can be automatically configured in execution pipelines, candidate results can be automatically scored and combined, and the system can learn from experience. Furthermore, our evaluation shows that the Medical Cognitive Apps are providing the correct results as they did for local execution and run in a reasonable amount of time.

Conclusion

The proposed solution is applicable to a variety of medical use cases and effectively supports the automated and self-adaptive configuration of cognitive pipelines based on medical interpretation algorithms.

Keywords

Computer aided medicine Semantic Web Phase recognition Tumor progression mapping Cognitive architecture 

Notes

Acknowledgments

This work was carried out with the support of the German Research Foundation (DFG) within projects I01, A01, R01, S01 and I04, SFB/TRR 125 “Cognition-Guided Surgery”.

Compliance with ethical standards

Conflict of interest

Patrick Philipp, Maria Maleshkova, Darko Katic, Christian Weber, Michael Götz, Stefanie Speidel, Achim Rettinger, Benedikt Kämpgen, Marco Nolden, Anna-Laura Wekerle, Rüdiger Dillmann, Hannes Kenngott, Beat Müller and Rudi Studer declare that they have no conflict of interest.

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Copyright information

© CARS 2015

Authors and Affiliations

  • Patrick Philipp
    • 1
    Email author
  • Maria Maleshkova
    • 1
  • Darko Katic
    • 2
  • Christian Weber
    • 4
  • Michael Götz
    • 4
  • Achim Rettinger
    • 1
  • Stefanie Speidel
    • 2
  • Benedikt Kämpgen
    • 1
  • Marco Nolden
    • 4
  • Anna-Laura Wekerle
    • 3
  • Rüdiger Dillmann
    • 2
  • Hannes Kenngott
    • 3
  • Beat Müller
    • 3
  • Rudi Studer
    • 1
  1. 1.Institute AIFB, Karlsruhe Institute of TechnologyKarlsruheGermany
  2. 2.Institute for Anthropomatics, Karlsruhe Institute of TechnologyKarlsruheGermany
  3. 3.Klinik für Allgemein-, Viszeral- und TransplantationschirurgieUniversity of HeidelbergHeidelbergGermany
  4. 4.Division of Medical and Biological InformaticsGerman Cancer Research Center (DKFZ)HeidelbergGermany

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