TY  - GEN
A1  - Goch, Caspar Jonas
N2  - 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 di?erent studies.
AV  - public
ID  - heidok17116
TI  - Expanding Graph Theoretical Indices to Include Medical Knowledge - 
An Assessment of Classi?cation Accuracy in the Case of Autism Spectrum Disorders
KW  - Network analysis
UR  - https://archiv.ub.uni-heidelberg.de/volltextserver/17116/
Y1  - 2014///
ER  -