@inproceedings{183be148f66b4d10bf39393c4b2b0c61,
title = "A prediction model for cognitive performance in health ageing using diffusion tensor imaging with graph theory",
abstract = "In this study, we employed diffusion tensor imaging (DTI) to construct brain structural network and then derive the connection matrices from 96 healthy elderly subjects. The correlation analysis between these topological properties of network based on graph theory and the Cognitive Abilities Screening Instrument (CASI) index were processed to extract the significant network characteristics. These characteristics were then integrated to estimate the models by various machine-learning algorithms to predict user's cognitive performance. From the results, linear regression model and Gaussian processes model showed presented better abilities with lower mean absolute errors of 5.8120 and 6.25 to predict the cognitive performance respectively. Moreover, these extracted topological properties of brain structural network derived from DTI also could be regarded as the bio-signatures for further evaluation of brain degeneration in healthy aged and early diagnosis of mild cognitive impairment (MCI).",
keywords = "Diffusion tensor imaging (DTI), Gaussian processes model, cognitive abilities screening instrument (CASI), graph theory, linear regression model, mild cognitive impairment (MCI)",
author = "Ruijuan Yun and Lin, \{Chung Chih\} and Shuicai Wu and Huang, \{Chu Chung\} and Lin, \{Ching Po\} and Chao, \{Yi Ping\}",
year = "2013",
doi = "10.1109/EMBC.2013.6609553",
language = "英语",
isbn = "9781457702167",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
pages = "527--530",
booktitle = "2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013",
note = "2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 ; Conference date: 03-07-2013 Through 07-07-2013",
}