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pro vyhledávání: '"Lee, Dong Soo"'
Autor:
Lee, Dong Soo, Kim, Hyun Joo, Huh, Youngmin, Kang, Yeon Koo, Whi, Wonseok, Lee, Hyekyoung, Kang, Hyejin
Voxel hierarchy on dynamic brain graphs is produced by k core percolation on functional dynamic amplitude correlation of resting-state fMRI. Directed graphs and their afferent/efferent capacities are produced by Markov modeling of the universal cover
Externí odkaz:
http://arxiv.org/abs/2406.08140
Autor:
Lee, Dong Soo1 (AUTHOR) dreamdoc77@catholic.ac.kr
Publikováno v:
Radiation Oncology. 8/13/2024, Vol. 19 Issue 1, p1-11. 11p.
Linear matrix factorizations (LMFs) such as independent component analysis (ICA), principal component analysis (PCA), and their extensions, have been widely used for finding relevant spatial maps in brain imaging data. The last step of an LMF before
Externí odkaz:
http://arxiv.org/abs/2110.06492
Autor:
Youk, Jeonghwan, Kwon, Hyun Woo, Lim, Joonoh, Kim, Eunji, Kim, Taewoo, Kim, Ryul, Park, Seongyeol, Yi, Kijong, Nam, Chang Hyun, Jeon, Sara, An, Yohan, Choi, Jinwook, Na, Hyelin, Lee, Eon-Seok, Cho, Youngwon, Min, Dong-Wook, Kim, HyoJin, Kang, Yeong-Rok, Choi, Si Ho, Bae, Min Ji, Lee, Chang Geun, Kim, Joon-Goon, Kim, Young Seo, Yu, Tosol, Lee, Won-Chul, Shin, Jong-Yeon, Lee, Dong Soo, Kim, Tae-You, Ku, Taeyun, Kim, Su Yeon, Lee, Joo-Hyeon, Koo, Bon-Kyoung, Lee, Hyunsook, Yi, On Vox, Han, Eon Chul, Chang, Ji Hyun, Kim, Kyung Su, Son, Tae Gen, Ju, Young Seok
Publikováno v:
In Cell Genomics 14 February 2024 4(2)
Akademický článek
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Autor:
Lee, Hyekyoung, Chung, Moo K., Choi, Hongyoon, Kang, Hyejin, Ha, Seunggyun, Kim, Yu Kyeong, Lee, Dong Soo
Persistent homology has been applied to brain network analysis for finding the shape of brain networks across multiple thresholds. In the persistent homology, the shape of networks is often quantified by the sequence of $k$-dimensional holes and Bett
Externí odkaz:
http://arxiv.org/abs/1811.04355
Akademický článek
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Autor:
Lee, Hyekyoung, Kim, Eunkyung, Kang, Hyejin, Huh, Youngmin, Lee, Youngjo, Lim, Seonhee, Lee, Dong Soo
Entropy is a classical measure to quantify the amount of information or complexity of a system. Various entropy-based measures such as functional and spectral entropies have been proposed in brain network analysis. However, they are less widely used
Externí odkaz:
http://arxiv.org/abs/1801.09257
Autor:
Bae, Hyo Jun, Kim, Seong-Hoon, Jeong, Yuseok, Park, Sungjin, Ochar, Kingsley, Hong, Youngsin, Seo, Yun Am, Ko, Baul, Bae, Jeong Hyang, Lee, Dong Soo, Choi, Inchan
Publikováno v:
Plants (2223-7747); Aug2024, Vol. 13 Issue 15, p2116, 14p