Seung‐Koo Lee - Concepedia

Author

Seung‐Koo Lee

Yonsei University ORCID

Also Known As

Eosu Kim, Ji Wang, Lee, Seok-Jin, Lee, Seung-Koo, Otgonbayar Tsedenbal, S K Lee, S LEE, S-K Lee, S-K. Lee, S. G. Lee

633

Publications

13.9K

Citations

H-Index

302

Concepts

All Affiliations

Yonsei University Severance Hospital Ewha Womans University Catholic University of Korea Korea University

About

Seung‐Koo Lee is an author at Yonsei University specializing in medicine, radiology, and neuroscience.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Medicine	37	89	4.4K
2	Engineering	20	35	1.4K
3	Health Sciences	18	30	1.6K
4	Social Sciences	13	13	589
5	Public Health	7	7	350

Seung‐Koo Lee

248

Publications

11.3K

Citations

H-Index

Page 1

	Year	Citations
Pediatric diffusion tensor imaging: Normal database and observation of the white matter maturation in early childhood Laurent Hermoye, Christine Saint‐Martin, Guy Cosnard, NeuroImage White Matter MaturationRadiologyMedical ImagingBrain StructureWhite Matter	2005	435
Federated learning enables big data for rare cancer boundary detection Sarthak Pati, Ujjwal Baid, Brandon Edwards, Nature Communications	2022	306
Clinical characteristics and outcomes of Takayasu's arteritis: analysis of 108 patients using standardized criteria for diagnosis, activity assessment, and angiographic classification Min‐Chan Park, Sang‐Won Lee, Park Yb, Scandinavian Journal of Rheumatology	2005	279
Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction Sohi Bae, Yoon Seong Choi, Sung Soo Ahn, Radiology Oncologic ImagingHigh-grade GliomasRadiomic FeaturesGliomaNeuro-oncology	2018	249
Elevated interleukin-10 levels correlated with disease activity in systemic lupus erythematosus. Y-B Park, Seung‐Koo Lee, D. S. Kim, PubMed	1998	248
Corpus callosal connection mapping using cortical gray matter parcellation and DT‐MRI Hae‐Jeong Park, Jae‐Jin Kim, Seung‐Koo Lee, Human Brain Mapping	2006	247
Fully automated hybrid approach to predict the<i>IDH</i>mutation status of gliomas via deep learning and radiomics Yoon Seong Choi, Sohi Bae, Jong Hee Chang, Neuro-Oncology	2020	230
Decreased number and function of endothelial progenitor cells in patients with migraine Sukkyung Lee, Kon Chu, Keun‐Hwa Jung, Neurology	2008	200
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging Yae Won Park, Jongmin Oh, Seng Chan You, European Radiology EngineeringMachine LearningMedical ImagingMagnetic Resonance ImagingBiomedical Imaging	2018	175
Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection Andréia V. Faria, Jiangyang Zhang, Kenichi Oishi, NeuroImage Automated Abnormality DetectionNeuroimaging ModalityBrain StructureDevelopmental Cognitive NeuroscienceComputational Neuroscience	2010	174

Page 1