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Machine learning approach to brain tumor detection and classification

Autor: Oh, Alice, Noh, Inyoung, Choo, Jian, Lee, Jihoo, Park, Justin, Hwang, Kate, Kim, Sanghyeon, Oh, Soo Min

Brain tumor detection and classification are critical tasks in medical image analysis, particularly in early-stage diagnosis, where accurate and timely detection can significantly improve treatment outcomes. In this study, we apply various statistica

Externí odkaz: http://arxiv.org/abs/2410.12692

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Exploring growing complex systems with higher-order interactions

Autor: Oh, Soo Min, Lee, Yongsun, Kahng, Byungnam

A complex system with many interacting individuals can be represented by a network consisting of nodes and links representing individuals and pairwise interactions, respectively. However, real-world systems grow with time and include many higher-orde

Externí odkaz: http://arxiv.org/abs/2410.06279

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Discontinuous emergence of a giant cluster in assortative scale-free networks

Autor: Jeong, Yeonsu, Oh, Soo Min, Cho, Young Sul

Publikováno v: J. Korean Phys. Soc. 81, 608 (2022)

A giant cluster emerges discontinuously in bond percolation in various networks when the growth of large clusters is globally suppressed. It was recently revealed that this phenomenon occurs even in a scale-free (SF) network, where hubs accelerate th

Externí odkaz: http://arxiv.org/abs/2205.11075

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Betweenness centrality of teams in social networks

Autor: Lee, Jongshin, Lee, Yongsun, Oh, Soo Min, Kahng, B.

Publikováno v: Chaos 31, 061108 (2021)

Betweenness centrality (BC) was proposed as an indicator of the extent of an individual's influence in a social network. It is measured by counting how many times a vertex (i.e., an individual) appears on all the shortest paths between pairs of verti

Externí odkaz: http://arxiv.org/abs/2105.06691

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Percolation Transitions in Growing Networks Under Achlioptas Processes: Analytic Solutions

Autor: Oh, Soo Min, Son, Seung-Woo, Kahng, Byungnam

Networks are ubiquitous in diverse real-world systems. Many empirical networks grow as the number of nodes increases with time. Percolation transitions in growing random networks can be of infinite order. However, when the growth of large clusters is

Externí odkaz: http://arxiv.org/abs/2012.10749

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Homological percolation transitions in growing simplicial complexes

Autor: Lee, Yongsun, Lee, Jongshin, Oh, Soo Min, Lee, Deokjae, Kahng, B.

Publikováno v: Chaos 31, 041102 (2021)

Simplicial complex (SC) representation is an elegant mathematical framework for representing the effect of complexes or groups with higher-order interactions in a variety of complex systems ranging from brain networks to social relationships. Here, w

Externí odkaz: http://arxiv.org/abs/2010.12224

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