Model Validation
A reliable model validation is crucial for the model’s corrections and, finally, clinical acceptance (3.3-R1.4.11). Similar to modeling, the appropriate data is often limited or unavailable. For an extensive model with only a small dataset, a reliable qua
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Development of Clinical Decision Support Systems using Bayesian Networks With an example of a MultiDisciplinary Treatment Decision for Laryngeal Cancer
Development of Clinical Decision Support Systems using Bayesian Networks
Mario A. Cypko
Development of Clinical Decision Support Systems using Bayesian Networks With an example of a MultiDisciplinary Treatment Decision for Laryngeal Cancer
Mario A. Cypko Innovation Center Computer Assisted Surgery, Medical Faculty University of Leipzig Leipzig, Germany Dissertation, University of Leipzig, 2017
ISBN 978-3-658-32593-0 ISBN 978-3-658-32594-7 (eBook) https://doi.org/10.1007/978-3-658-32594-7 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer Vieweg imprint is published by the registered company Springer Fachmedien Wiesbaden GmbH part of Springer Nature. The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany
”If I have seen further, it is by standing on the shoulders of giants.” — Isaac Newton, 1676
Acknowledgments This thesis combines multiple technical and clinical disciplines and never could have reached this level without the support and many inspiring discussions with giants of various professions. Those who are not personally named here but crossed my scientific journey, you influenced my work as well, thank you. Personally, first and foremost, I would like to thank my supervisors Prof. Heinz U. Lemke and Prof. Andreas Dietz as well as my thesis supporter Prof. Gerhard Brewka. Heinz Lemke was the visionary of ICCAS’s digital patient model project and senior advisor of the Digital Patient and Process Model group. Dear Heinz, thank you for sharing your knowledge, experiences and visions. Thank y
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