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Know-GRRF: Domain-Knowledge Informed Biomarker Discovery with Random Forests Read chapter Read first chapter

2018 | OriginalPaper | Chapter

A Transferable Belief Model Decision Support Tool over Complementary Clinical Conditions

Authors : Abderraouf Hadj Henni, David Pasquier, Nacim Betrouni

Published in: Bioinformatics and Biomedical Engineering

Publisher: Springer International Publishing

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Abstract

This paper presents an algorithm for decision support over two complementary clinical conditions given a large features data base. The algorithm is mainly divided in two parts, the first one aims at identifying relevant features from a large dimension data base using a heuristic method based on a discriminating power. The second part is a tool based on the Transferable Belief Model (TBM) which combines information extracted from the selected features to provide decision results with probabilities along with a result’s consistency measure so that decision could be made carefully. The proposed algorithm is tested on a downloaded feature data base. The TBM based decision support tool showed consistent results w.r.t provided outcomes by combining data from two relevant features identified after using the heuristic feature ranking method.

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Appendix
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Metadata
Title
A Transferable Belief Model Decision Support Tool over Complementary Clinical Conditions
Authors
Abderraouf Hadj Henni
David Pasquier
Nacim Betrouni
Copyright Year
2018
Book
Bioinformatics and Biomedical Engineering

Print ISBN: 978-3-319-78758-9

Electronic ISBN: 978-3-319-78759-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-78759-6_37

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