MinKyu Kang

Prof. MinKyu Kang

Yeungnam University College of Medicine
orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 September 2021 in Nature Medicine
Verified
Journal Article
Closed access
PDF file
IDIttai Dayan
Ittai Dayan
HRHolger Roth
Holger Roth
AZAoxiao Zhong
Aoxiao Zhong
AHAhmed Harouni
Ahmed Harouni
AGAmilcare Gentili
Amilcare Gentili
QLQuanzheng Li
Quanzheng Li

1 May 2021 in Medical Image Analysis
Verified
Journal Article
Closed access
AZAoxiao Zhong
Aoxiao Zhong
XLXiang Li
Xiang Li
DWDufan Wu
Dufan Wu
HRHui Ren
Hui Ren
KKKyungsang Kim
Kyungsang Kim
Quanzheng LiQuanzheng Li
Quanzheng Li

25 March 2021 in Alimentary Pharmacology & Therapeutics
Verified
Journal Article
Closed access
JPJung Gil Park
Jung Gil Park
JJJinho Jung
Jinho Jung
KVKritin K. Verma
Kritin K. Verma
MKMinKyu Kang
MinKyu Kang
EMEgbert Madamba
Egbert Madamba
RLRohit Loomba
Rohit Loomba

15 May 2020 in Nutrients
Verified
Journal Article
Open access
PDF file
JPJung Gil Park
Jung Gil Park
WTWon Young Tak
Won Young Tak
JPJun Yong Park
Jun Yong Park
YKYoung Oh Kweon
Young Oh Kweon
WCWoo Jin Chung
Woo Jin Chung
WLWon Kee Lee
Won Kee Lee
Background and Aims: Clinical evidence for the benefits of branched-chain amino acids (BCAAs) is lacking in advanced liver disease. We evaluated the potential benefits of long-term oral BCAA supplementation in patients with advanced liver disease. Methods: Liver cirrhosis patients with Child–Pugh (CP) scores from 8 to 10 were prospectively recruited from 13 medical centers. Patients supplemented with 12.45 g of daily BCAA granules over 6 months, and patients consuming a regular diet were assigned to the BCAA and control groups, respectively. The effects of BCAA supplementation were evaluated using the model for end-stage liver disease (MELD) score, CP score, serum albumin, serum bilirubin, incidence of cirrhosis-related events, and event-free survival for 24 months. Results: A total of 124 patients was analyzed: 63 in the BCAA group and 61 in the control group. The MELD score (p = 0.009) and CP score (p = 0.011) significantly improved in the BCAA group compared to the control group over time. However, the levels of serum albumin and bilirubin in the BCAA group did not improve during the study period. The cumulative event-free survival was significantly improved in the BCAA group compared to the control group (HR = 0.389, 95% CI = 0.221–0.684, p < 0.001). Conclusion: Long-term supplementation with oral BCAAs can potentially improve liver function and reduce major complications of cirrhosis in patients with advanced liver disease.

13 May 2020 in Genes
Verified
Journal Article
Open access
PDF file
MHMan-Hoon Han
Man-Hoon Han
JLJee Hyun Lee
Jee Hyun Lee
GKGyeonghwa Kim
Gyeonghwa Kim
ELEunhye Lee
Eunhye Lee
YLYu Rim Lee
Yu Rim Lee
Keun HurKeun Hur
Keun Hur
Background: Advanced liver fibrosis is the most important prognostic factor in nonalcoholic fatty liver disease (NAFLD). The long noncoding RNA (lncRNA), growth arrest-specific transcript 5 (GAS5), is associated with the inhibition of liver fibrogenesis, and its levels are decreased in cirrhotic liver. Methods: We analyzed 51 patients with NAFLD, the diagnosis of which was confirmed by liver biopsy. Expression of GAS5 in both the liver and plasma of the patients was analyzed using a quantitative real-time polymerase chain reaction according to the fibrosis stage. Results: Plasma GAS5 expression was significantly higher in patients with advanced fibrosis than in those without. As the fibrosis progressed, GAS5 expression in plasma increased, with the exception of that in cirrhotic livers. Plasma levels of GAS5 were lower in patients with cirrhosis than in those with advanced fibrosis. Conclusion: Elevated circulating levels of the lncRNA GAS5 are associated with the progression of liver fibrosis prior to the development of cirrhosis.

12 October 2020 in IEEE Journal of Biomedical and Health Informatics
Verified
Journal Article
Closed access
DWDufan Wu
Dufan Wu
KGKuang Gong
Kuang Gong
CAChiara Daniela Arru
Chiara Daniela Arru
FHFatemeh Homayounieh
Fatemeh Homayounieh
BBBernardo C. Bizzo
Bernardo C. Bizzo
Quanzheng LiQuanzheng Li
Quanzheng Li
Early and accurate diagnosis of Coronavirus disease (COVID-19) is essential for patient isolation and contact tracing so that the spread of infection can be limited. Computed tomography (CT) can provide important information in COVID-19, especially for patients with moderate to severe disease as well as those with worsening cardiopulmonary status. As an automatic tool, deep learning methods can be utilized to perform semantic segmentation of affected lung regions, which is important to establish disease severity and prognosis prediction. Both the extent and type of pulmonary opacities help assess disease severity. However, manually pixel-level multi-class labelling is time-consuming, subjective, and non-quantitative. In this work, we proposed a hybrid weak label-based deep learning method that utilize both the manually annotated pulmonary opacities from COVID-19 pneumonia and the patient-level disease-type information available from the clinical report. A UNet was firstly trained with semantic labels to segment the total infected region. It was used to initialize another UNet, which was trained to segment the consolidations with patient-level information using the Expectation-Maximization (EM) algorithm. To demonstrate the performance of the proposed method, multi-institutional CT datasets from Iran, Italy, South Korea, and the United States were utilized. Results show that our proposed method can predict the infected regions as well as the consolidation regions with a good correlation to human annotation.