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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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Shear Wave Elastography for Assessment of Steatohepatitis and Hepatic Fibrosis in Rat Models of Non-Alcoholic Fatty Liver Disease.

TL;DR: SWE is a potential non-invasive method for the detection of NASH and staging of hepatic fibrosis in patients with NAFLD and was effective in detecting non-alcoholic steatohepatitis (NASH) and in determining fibrosis stage.
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Clinical implications of mucinous components correlated with microsatellite instability in patients with colorectal cancer

TL;DR: The purpose of this study was to evaluate the association of MSI with clinicopathological features and the oncological outcome in patients with a mucinous component of CRC with microsatellite instability.
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Post-resection Prognosis of Combined Hepatocellular Carcinoma-Cholangiocarcinoma According to the 2010 WHO Classification

TL;DR: The results indicated that there would be close relationship between the post-resection prognosis and histological types according to the 2010 WHO classification, but these Histological types did not become an independent prognostic factor.
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Reconsideration of the Histologic Definitions Used in the Pathologic Staging of Extrahepatic Bile Duct Carcinoma

TL;DR: The bile duct wall is more precisely defined as occurring between the mucosa and the outermost boundary of dense fibromuscular tissue, without consideration of the presence or absence of blood vessels and nerve fibers.
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Validation of the Eighth American Joint Committee on Cancer Staging System for Distal Bile Duct Carcinoma.

TL;DR: The T andN categories of the eighth edition AJCC staging system for DBDC accurately predict patient prognosis and could distinguish patient survival by both pairwise and overall comparisons.