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Expanding Graph Theoretical Indices to Include Medical Knowledge - An Assessment of Classification Accuracy in the Case of Autism Spectrum Disorders

Goch, Caspar Jonas

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Download (6MB) | Lizenz: Creative Commons LizenzvertragExpanding Graph Theoretical Indices to Include Medical Knowledge - An Assessment of Classification Accuracy in the Case of Autism Spectrum Disorders by Goch, Caspar Jonas underlies the terms of Creative Commons Attribution 3.0 Deutschland

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Abstract

Using graph theory to analyse the architecture of the human brain, the connectome, has gained increasing interest in the last decade. In this work we extend graph measures, which have previously been developed for other applications, to include prior medical information. These extended measures are then evaluated on a collective of Autism Spectrum Disorder patients. Examining their performance in comparison to other traditionally used measures we show, that they are a valuable new tool in the analysis of the human connectome. We then further evaluate their performance over a range of network densities in order to determine the range at which they supply the most valuable information. By doing an in depth evaluation of these measures we aim to reduce the amount of guesswork in choosing variables in the analysis of the connectome and help to improve the comparability of different studies.

Item Type: Dissertation
Supervisor: Oelfke, Prof. Dr. Uwe
Date of thesis defense: 2 July 2014
Date Deposited: 10 Jul 2014 07:54
Date: 2014
Faculties / Institutes: The Faculty of Physics and Astronomy > Dekanat der Fakultät für Physik und Astronomie
Service facilities > German Cancer Research Center (DKFZ)
Subjects: 004 Data processing Computer science
530 Physics
610 Medical sciences Medicine
Controlled Keywords: Medical Imaging
Uncontrolled Keywords: Network analysis
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