S
Seung-Mo Hong
Researcher at University of Ulsan
Publications - 383
Citations - 21628
Seung-Mo Hong is an academic researcher from University of Ulsan. The author has contributed to research in topics: Pancreatic cancer & Cancer. The author has an hindex of 53, co-authored 361 publications receiving 17907 citations. Previous affiliations of Seung-Mo Hong include University of Virginia Health System & Johns Hopkins University School of Medicine.
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Lesion localization in patients with hyperparathyroidism using double-phase Tc-99m MIBI parathyroid scintigraphy
Jung Woo Shin,Jin-Sook Ryu,Jae Seung Kim,Dae Hyuk Moon,Seung-Mo Hong,Gyung Yub Gong,S. Hong,Hee Kyung Lee +7 more
TL;DR: Evaluating the diagnostic usefulness of double-phase Tc-99m MIBI parathyroid scintigraphy with single photon emission computed tomography (SPECT) in patients with hyper-parathyroidism found both adenomas and hyperplasias showed significantly increased oxyphil cell contents compared with normalParathyroid glands.
Posted Content
Identification of Outlying Observations with Quantile Regression for Censored Data
TL;DR: Three outlier detection algorithms based on censored quantile regression are proposed, two of which are modified versions of existing algorithms for uncensored or censored data, while the third is a newly developed algorithm to overcome the demerits of previous approaches.
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Postresection prognosis of combined hepatocellular carcinoma-cholangiocarcinoma according to the 2010 World Health Organization classification: single-center experience of 168 patients.
Minjae Kim,Shin Hwang,Chul-Soo Ahn,Ki-Hun Kim,Deok-Bog Moon,Tae-Yong Ha,Gi-Won Song,Dong-Hwan Jung,Gil-Chun Park,Seung-Mo Hong +9 more
TL;DR: In this article, the effects of combined hepatocellular carcinoma and cholangiocarcinoma (cHCC-CC) histology, according to the 2010 World Health Organization (WHO) classification, on patient prognosis were investigated.
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Profiling of conditionally reprogrammed cell lines for in vitro chemotherapy response prediction of pancreatic cancer
Hee Seung Lee,Eun Young Kim,Jin-Young Lee,Seung Joon Park,Ho Kyoung Hwang,Chan Hee Park,Se Young Jo,Chang Moo Kang,Seung-Mo Hong,Huapyong Kang,Jung Hyun Jo,In Rae Cho,Moon Jae Chung,Jeong Youp Park,Seung Woo Park,Si Young Song,Jung Min Han,Sangwoo Kim,Seungmin Bang +18 more
TL;DR: In this article, conditionally reprogrammed cells (CRCs) were used to establish patient-derived models for pancreatic ductal adenocarcinoma (PDAC) and perform genetic analysis with responses to anticancer drug.
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A Clinically Applicable 24-Protein Model for Classifying Risk Subgroups in Pancreatic Ductal Adenocarcinomas using Multiple Reaction Monitoring-Mass Spectrometry
Minsoo Son,Hongbeom Kim,Dohyun Han,Yoseop Kim,Iksoo Huh,Youngmin Han,Seung-Mo Hong,Wooil Kwon,Haeryoung Kim,Jin-Young Jang,Youngsoo Kim +10 more
TL;DR: In this paper, the authors identified 24 protein features that could classify the four risk subgroups associated with patient outcomes: stable, exocrine-like; activated, and extracellular matrix (ECM) remodeling.