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Development of Clinical Decision Support Systems using Bayesian Networks

With an example of a Multi-Disciplinary Treatment Decision for Laryngeal Cancer

  • Book
  • © 2020

Overview

Authors:
  1. Mario A. Cypko

    1. Innovation Center Computer Assisted Surgery, Medical Faculty, University of Leipzig, Leipzig, Germany

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  • New opportunities for completely transparent and reproducible CDSS

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Table of contents (11 chapters)

  1. Front Matter

    Pages I-XIX
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  2. Basic Consideration

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • Mario A. Cypko
      Pages 3-5

    3. Tumor Board Decision for Larynx Cancer Patients

      • Mario A. Cypko
      Pages 7-14

    4. Development of a Clinical Decision Support System

      • Mario A. Cypko
      Pages 15-26

    5. Clinical Decision Model using Bayesian Networks

      • Mario A. Cypko
      Pages 27-46

  3. Therapy Decision Support System using Bayesian Networks

    1. Front Matter

      Pages 47-47
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    2. Patient-specific Bayesian Network in a Clinical Environment

      • Mario A. Cypko
      Pages 49-56

    3. TreLynCa: A Tumor Board Decision Model for Laryngeal Cancer

      • Mario A. Cypko
      Pages 57-68

    4. Model Validation

      • Mario A. Cypko
      Pages 69-79

    5. Tools for Guided BN Modeling

      • Mario A. Cypko
      Pages 81-102

    6. GUI for PSBN-based decision verification

      • Mario A. Cypko
      Pages 103-117

  4. Conclusion

    1. Front Matter

      Pages 119-119
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    2. Summary

      • Mario A. Cypko
      Pages 121-121

    3. Appraisal and Future Work

      • Mario A. Cypko
      Pages 123-127

  5. Back Matter

    Pages 129-148
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Keywords

About this book

For the development of clinical decision support systems based on Bayesian networks, Mario A. Cypko investigates comprehensive expert models of multidisciplinary clinical treatment decisions and solves challenges in their modeling. The presented methods, models and tools are developed in close and intensive cooperation between knowledge engineers and clinicians. In the course of this study, laryngeal cancer serves as an exemplary treatment decision. The reader is guided through a development process and new opportunities for research and development are opened up: in modeling and validation of workflows, guided modeling, semi-automated modeling, advanced Bayesian networks, model-user interaction, inter-institutional modeling and quality management.

Authors and Affiliations

  • Innovation Center Computer Assisted Surgery, Medical Faculty, University of Leipzig, Leipzig, Germany

    Mario A. Cypko

About the author

Dr.-Ing. Mario A. Cypko completed his PhD at the Computer Science department of the University of Leipzig, Germany. He was a postdoctoral research fellow in the Human Research Office of the European Space Agency in the Netherlands. He is currently a postdoctoral research assistant at the German Heart Center Berlin, Germany.

Bibliographic Information

  • Book Title: Development of Clinical Decision Support Systems using Bayesian Networks

  • Book Subtitle: With an example of a Multi-Disciplinary Treatment Decision for Laryngeal Cancer

  • Authors: Mario A. Cypko

  • DOI: https://doi.org/10.1007/978-3-658-32594-7

  • Publisher: Springer Vieweg Wiesbaden

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020

  • Softcover ISBN: 978-3-658-32593-0Published: 01 December 2020

  • eBook ISBN: 978-3-658-32594-7Published: 30 November 2020

  • Edition Number: 1

  • Number of Pages: XIX, 148

  • Number of Illustrations: 29 b/w illustrations, 10 illustrations in colour

  • Topics: Knowledge based Systems, Computer Applications, Artificial Intelligence, Quality of Life Research

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