Zobrazeno 1 - 10
of 446
pro vyhledávání: '"Hae Jeong, Park"'
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0298740 (2024)
In this research, we employed functional magnetic resonance imaging (fMRI) to examine the neurological basis for understanding wh-questions in wh-in-situ languages such as Korean, where wh-elements maintain their original positions instead of moving
Externí odkaz:
https://doaj.org/article/c43fcf4c83294dfb9cdb2e1759926a36
Neural processing of prototypicality and simplicity of product design in forming design preferences.
Publikováno v:
PLoS ONE, Vol 19, Iss 1, p e0297148 (2024)
The current study investigates the neural correlates when processing prototypicality and simplicity-affecting the preference of product design. Despite its significance, not much is known about how our brain processes these visual qualities of design
Externí odkaz:
https://doaj.org/article/fcc490eb44064818a2f5ac10c421a133
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Artificial intelligence (AI) using deep learning approaches the capabilities of human experts in medical image diagnosis. However, due to liability issues in medical decisions, AI is often relegated to an assistant role. Based on this respon
Externí odkaz:
https://doaj.org/article/0b4085984e654baba11c6d4d40f0de88
Publikováno v:
NeuroImage, Vol 275, Iss , Pp 120161- (2023)
The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and
Externí odkaz:
https://doaj.org/article/e127de602b9f4c0baa18d35e5c837e69
Autor:
Kisung You, Hae-Jeong Park
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract The correlation matrix is a typical representation of node interactions in functional brain network analysis. The analysis of the correlation matrix to characterize brain networks observed in several neuroimaging modalities has been conducte
Externí odkaz:
https://doaj.org/article/5f238780a8c1401186ee2b699347ea38
Autor:
Jae Chan Choi, Hae-Jeong Park, Jeong A. Park, Dae Ryong Kang, Young-Seok Choi, SoHyun Choi, Hong Gyu Lee, Jun-Ho Choi, In-Ho Choi, Min Woo Yoon, Jong-Min Lee, Jinhee Kim
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract Prior experiences of successful and failed treatments are known to influence the efficacy of a newly applied treatment. However, whether that carry-over effect applies to non-pharmacological treatments is unknown. This study investigated how
Externí odkaz:
https://doaj.org/article/40adeaf511504fd4b7aaf16b81f05fb5
Autor:
Jongsoo Baek, Hae-Jeong Park
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
Abstract Most psychological experiments measure human cognitive function through the response time and accuracy of the response to a set of stimuli. Since response time and accuracy complement each other, it is often difficult to interpret cognitive
Externí odkaz:
https://doaj.org/article/749ac5cd5e314f87b7a25dfc677657e6
Autor:
Dongha Lee, Hae-Jeong Park
Publikováno v:
NeuroImage, Vol 254, Iss , Pp 119167- (2022)
The white matter in the brain is composed of neural fibers that wire the cortical and subcortical brain systems. Considering the complexity in terms of interconnections of many neural populations within the narrow space surrounded by the folding wall
Externí odkaz:
https://doaj.org/article/53a0529691c44b03b423f658c8c2fe39
Publikováno v:
PLoS ONE, Vol 17, Iss 6, p e0269376 (2022)
We explore potential cross-informant discrepancies between child- and parent-report measures with an example of the Child Behavior Checklist (CBCL) and the Youth Self Report (YSR), parent- and self-report measures on children's behavioral and emotion
Externí odkaz:
https://doaj.org/article/2b567a7e11fb4e699e862feaac871666
Autor:
Dongchul Cha, Chongwon Pae, Se A Lee, Gina Na, Young Kyun Hur, Ho Young Lee, A Ra Cho, Young Joon Cho, Sang Gil Han, Sung Huhn Kim, Jae Young Choi, Hae-Jeong Park
Publikováno v:
JMIR Medical Informatics, Vol 9, Iss 12, p e33049 (2021)
BackgroundDeep learning (DL)–based artificial intelligence may have different diagnostic characteristics than human experts in medical diagnosis. As a data-driven knowledge system, heterogeneous population incidence in the clinical world is conside
Externí odkaz:
https://doaj.org/article/4621df219b094013ac34c6e13d808523