Ho‐Chan Cho

1.1k total citations
34 papers, 353 citations indexed

About

Ho‐Chan Cho is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Surgery. According to data from OpenAlex, Ho‐Chan Cho has authored 34 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Endocrinology, Diabetes and Metabolism, 11 papers in Molecular Biology and 9 papers in Surgery. Recurrent topics in Ho‐Chan Cho's work include Adipokines, Inflammation, and Metabolic Diseases (7 papers), Pancreatic function and diabetes (6 papers) and Metabolism, Diabetes, and Cancer (5 papers). Ho‐Chan Cho is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (7 papers), Pancreatic function and diabetes (6 papers) and Metabolism, Diabetes, and Cancer (5 papers). Ho‐Chan Cho collaborates with scholars based in South Korea, United States and Nigeria. Ho‐Chan Cho's co-authors include Dae‐Kyu Song, Seung‐Soon Im, Jae‐Hyung Park, Jae‐Hoon Bae, In‐Sung Chung, Sung-Hee Park, Ki‐Cheor Bae, Jin Han, Jung‐Won Choi and Sang Woo Kim and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Scientific Reports.

In The Last Decade

Ho‐Chan Cho

32 papers receiving 350 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ho‐Chan Cho South Korea	12	138	86	78	67	66	34	353
Romina Vargas Chile	13	173 1.3×	103 1.2×	73 0.9×	62 0.9×	149 2.3×	23	478
Adi Drori Israel	10	90 0.7×	110 1.3×	109 1.4×	118 1.8×	45 0.7×	13	446
Uthra Rajamani United States	10	138 1.0×	77 0.9×	53 0.7×	48 0.7×	53 0.8×	13	319
Daniela Tomie Furuya Brazil	13	196 1.4×	144 1.7×	100 1.3×	120 1.8×	87 1.3×	16	476
Ankit Gilani United States	10	123 0.9×	72 0.8×	96 1.2×	33 0.5×	57 0.9×	20	347
Suzan Tabur Türkiye	12	96 0.7×	53 0.6×	140 1.8×	52 0.8×	38 0.6×	36	424
Cynthia C. Greenberg United States	8	221 1.6×	93 1.1×	42 0.5×	78 1.2×	38 0.6×	10	449
Paz Vital Mexico	7	104 0.8×	79 0.9×	89 1.1×	39 0.6×	30 0.5×	7	353
C. Di Filippo Italy	11	105 0.8×	74 0.9×	43 0.6×	67 1.0×	37 0.6×	14	406
Pablo Cabral United States	12	160 1.2×	142 1.7×	144 1.8×	42 0.6×	109 1.7×	23	435

Countries citing papers authored by Ho‐Chan Cho

Since Specialization

Citations

This map shows the geographic impact of Ho‐Chan Cho's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ho‐Chan Cho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ho‐Chan Cho more than expected).

Fields of papers citing papers by Ho‐Chan Cho

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ho‐Chan Cho. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ho‐Chan Cho. The network helps show where Ho‐Chan Cho may publish in the future.

Co-authorship network of co-authors of Ho‐Chan Cho

This figure shows the co-authorship network connecting the top 25 collaborators of Ho‐Chan Cho. A scholar is included among the top collaborators of Ho‐Chan Cho based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ho‐Chan Cho. Ho‐Chan Cho is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kim, Ji‐Hyun, Kwang Joon Kim, In‐Cheol Kim, et al.. (2025). Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: a prospective observational study. BMJ Health & Care Informatics. 32(1). e101353–e101353. 1 indexed citations

Kim, Ji‐Hyun, Kwang Joon Kim, In‐Cheol Kim, et al.. (2025). Prospective external validation of a deep-learning-based early-warning system for major adverse events in general wards in South Korea. Acute and Critical Care. 40(2). 197–208. 1 indexed citations

Cho, Eunyoung, Young‐Seon Jeong, Ji‐Hyun Kim, et al.. (2025). Preserving Informative Presence: How Missing Data and Imputation Strategies Affect the Performance of an AI-Based Early Warning Score. Journal of Clinical Medicine. 14(7). 2213–2213. 1 indexed citations

Jung, Kyong Yeun, So Yeon Park, Eu Jeong Ku, et al.. (2025). Clinical Utility of Salivary Steroid Profiling for the Differential Diagnosis of Adrenal Diseases. The Journal of Clinical Endocrinology & Metabolism. 111(3). e827–e836. 1 indexed citations

Cho, Jooyoung, Ho‐Chan Cho, Ohk‐Hyun Ryu, et al.. (2024). Reference Standards for C-Peptide in Korean Population: A Korean Endocrine Hormone Reference Standard Data Center Study. Endocrinology and Metabolism. 39(3). 489–499. 1 indexed citations

Park, Jae‐Hyung, et al.. (2024). Identification of Adipsin as a Biomarker of Beta Cell Function in Patients with Type 2 Diabetes. Journal of Clinical Medicine. 13(23). 7351–7351.

Park, Hyeong Kyu, Kyoung‐Ah Kim, Tae Seo Sohn, et al.. (2023). Effects of dapagliflozin compared with glimepiride on body composition in Asian patients with type 2 diabetes inadequately controlled with metformin: The BEYOND study. Diabetes Obesity and Metabolism. 25(9). 2743–2755. 3 indexed citations

Jeong, In‐Kyung, Juneyoung Lee, Ho‐Chan Cho, et al.. (2022). Current Status of Low-Density Lipoprotein Cholesterol Target Achievement in Patients with Type 2 Diabetes Mellitus in Korea Compared with Recent Guidelines. Diabetes & Metabolism Journal. 46(3). 464–475. 9 indexed citations

Choi, Dughyun, Haekyung Lee, Jin Seok Jeon, et al.. (2022). Weight Change Alters the Small RNA Profile of Urinary Extracellular Vesicles in Obesity. Obesity Facts. 15(2). 292–301. 3 indexed citations

10.

Bae, Yun‐Ui, et al.. (2021). Association of Protein Z with Prediabetes and Type 2 Diabetes. Endocrinology and Metabolism. 36(3). 637–646. 1 indexed citations

11.

Moon, Seong‐Su, Chong Hwa Kim, Seon Mee Kang, et al.. (2020). Status of Diabetic Neuropathy in Korea: A National Health Insurance Service-National Sample Cohort Analysis (2006 to 2015). Diabetes & Metabolism Journal. 45(1). 115–119. 12 indexed citations

12.

Han, Eugene, et al.. (2020). Comparison of Serum PCSK9 Levels in Subjects with Normoglycemia, Impaired Fasting Glucose, and Impaired Glucose Tolerance. Endocrinology and Metabolism. 35(2). 480–483. 4 indexed citations

13.

Im, Seung‐Soon, Jong Cheol Shon, In‐Sung Chung, et al.. (2019). Plasma sphingomyelins increase in pre-diabetic Korean men with abdominal obesity. PLoS ONE. 14(3). e0213285–e0213285. 25 indexed citations

14.

Kim, Sang Woo, Jung‐Won Choi, Jong Won Yun, et al.. (2019). Proteomics approach to identify serum biomarkers associated with the progression of diabetes in Korean patients with abdominal obesity. PLoS ONE. 14(9). e0222032–e0222032. 38 indexed citations

15.

Kang, Hye Suk, Ho‐Chan Cho, Jae‐Ho Lee, et al.. (2016). Metformin stimulates IGFBP-2 gene expression through PPARalpha in diabetic states. Scientific Reports. 6(1). 23665–23665. 41 indexed citations

16.

Park, Jae‐Hyung, Yoon Jung Choi, Yong Woon Kim, et al.. (2013). Green tea extract with polyethylene glycol-3350 reduces body weight and improves glucose tolerance in db/db and high-fat diet mice. Naunyn-Schmiedeberg s Archives of Pharmacology. 386(8). 733–745. 6 indexed citations

17.

Cho, Ho‐Chan, Yun‐Kyeong Cho, Hyoung‐Seob Park, et al.. (2012). Association of promoter region single nucleotide polymorphisms at positions −819C/T and −592C/A of interleukin 10 gene with ischemic heart disease. Inflammation Research. 61(8). 899–905. 20 indexed citations

18.

Sung, Hye‐Young, Young Sung Suh, Ho‐Chan Cho, et al.. (2010). Role of (−)-epigallocatechin-3-gallate in cell viability, lipogenesis, and retinol-binding protein 4 expression in adipocytes. Naunyn-Schmiedeberg s Archives of Pharmacology. 382(4). 303–310. 22 indexed citations

19.

Jung, Yuna, Kyeong‐Min Lee, Mi-Kyung Kim, et al.. (2009). Forkhead transcription factor FoxO1 inhibits insulin- and transforming growth factor-β-stimulated plasminogen activator inhibitor-1 expression. Biochemical and Biophysical Research Communications. 386(4). 757–761. 10 indexed citations

20.

Park, Sung-Hee, Jae‐Hoon Bae, Ho‐Chan Cho, et al.. (2007). Uncoupling by (−)-epigallocatechin-3-gallate of ATP-sensitive potassium channels from phosphatidylinositol polyphosphates and ATP. Pharmacological Research. 56(3). 237–247. 25 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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