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@proceedings{2397962, author = {Gajdoš, Martin and Nováková, Marie and Lamoš, Martin and Říha, Pavel and Rektorová, Irena and Mikl, Michal}, booktitle = {Czech – Austrian Workshop on Magnetic Resonance Imaging and Spectroscopy, 2023, Znojmo}, keywords = {Amnestic mild cognitive impairment; dynamic functional connectivity; sliding window analysis;}, language = {eng}, title = {State analysis of fMRI in amnestic mild cognitive impairment}, url = {https://mrs.ikem.cz/en/blog/mezinarodni-seminar-o-magneticke-resonanci-czech-austrian-workshop-on-magnetic-resonance-imaging-and-spectroscopy-2023}, year = {2023} }
TY - CONF ID - 2397962 AU - Gajdoš, Martin - Nováková, Marie - Lamoš, Martin - Říha, Pavel - Rektorová, Irena - Mikl, Michal PY - 2023 TI - State analysis of fMRI in amnestic mild cognitive impairment KW - Amnestic mild cognitive impairment KW - dynamic functional connectivity KW - sliding window analysis; UR - https://mrs.ikem.cz/en/blog/mezinarodni-seminar-o-magneticke-resonanci-czech-austrian-workshop-on-magnetic-resonance-imaging-and-spectroscopy-2023 N2 - Amnestic mild cognitive impairment (aMCI) is transitional state between normal aging and early dementia. In this work, we studied dynamic functional connectivity captured with sliding window analysis, whoch was performed on a dataset of 76 subjects (38 HC + 38 aMCI). We found significant differences in coverage in 2 out of 4 identified states. Moreover, with support vector machine, we were able to discriminate between these two groups with approx. 95% accuracy. In future work, we plan to crossvalidate presented classifier. Amnestic mild cognitive impairment (aMCI) is transitional state between normal aging and early dementia. In this work, we studied dynamic functional connectivity captured with sliding window analysis, whoch was performed on a dataset of 76 subjects (38 HC + 38 aMCI). We found significant differences in coverage in 2 out of 4 identified states. Moreover, with support vector machine, we were able to discriminate between these two groups with approx. 95% accuracy. In future work, we plan to crossvalidate presented classifier. ER -
GAJDOŠ, Martin, Marie NOVÁKOVÁ, Martin LAMOŠ, Pavel ŘÍHA, Irena REKTOROVÁ a Michal MIKL. State analysis of fMRI in amnestic mild cognitive impairment. In \textit{Czech – Austrian Workshop on Magnetic Resonance Imaging and Spectroscopy, 2023, Znojmo}. 2023.
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