Chun‐Heng Kuo

408 total citations
25 papers, 259 citations indexed

About

Chun‐Heng Kuo is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism and Obstetrics and Gynecology. According to data from OpenAlex, Chun‐Heng Kuo has authored 25 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cardiology and Cardiovascular Medicine, 10 papers in Endocrinology, Diabetes and Metabolism and 9 papers in Obstetrics and Gynecology. Recurrent topics in Chun‐Heng Kuo's work include Gestational Diabetes Research and Management (8 papers), Pregnancy and preeclampsia studies (6 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers). Chun‐Heng Kuo is often cited by papers focused on Gestational Diabetes Research and Management (8 papers), Pregnancy and preeclampsia studies (6 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers). Chun‐Heng Kuo collaborates with scholars based in Taiwan and Italy. Chun‐Heng Kuo's co-authors include Hung‐Yuan Li, Szu‐Chi Chen, Chien‐Nan Lee, Lee‐Ming Chuang, Shin‐Yu Lin, Kuan‐Yu Chen, Kang‐Chih Fan, Ming‐Wei Lin, Chung‐Ze Wu and Jung‐Nan Wei and has published in prestigious journals such as PLoS ONE, Diabetes Care and Scientific Reports.

In The Last Decade

Chun‐Heng Kuo

21 papers receiving 253 citations

Peers

Chun‐Heng Kuo

SURGE

PPCH

EDM

CCM

Szu‐Chi Chen Taiwan

Jas‐mine Seah Australia

Jianbin Sun China

Christine Ang United Kingdom

Olimpia Diadei Italy

Jorge Dores Portugal

Luis Alberto Concepción‐Urteaga Peru

J Robinson United States

Andrew Hartland United Kingdom

Amit Mayer Israel

Szu‐Chi Chen Taiwan

Chun‐Heng Kuo

113 ×0.8

76 ×0.9

SURGE

51 ×0.9

PPCH

78 ×2.4

EDM

19 ×0.7

CCM

Citations per year, relative to Chun‐Heng Kuo Chun‐Heng Kuo (= 1×) peers Szu‐Chi Chen

Countries citing papers authored by Chun‐Heng Kuo

Since Specialization

Citations

This map shows the geographic impact of Chun‐Heng Kuo'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 Chun‐Heng Kuo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun‐Heng Kuo more than expected).

Fields of papers citing papers by Chun‐Heng Kuo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun‐Heng Kuo. 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 Chun‐Heng Kuo. The network helps show where Chun‐Heng Kuo may publish in the future.

Co-authorship network of co-authors of Chun‐Heng Kuo

This figure shows the co-authorship network connecting the top 25 collaborators of Chun‐Heng Kuo. A scholar is included among the top collaborators of Chun‐Heng Kuo 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 Chun‐Heng Kuo. Chun‐Heng Kuo 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

Wu, Jia‐Ling, et al.. (2025). Nationwide singleton birth weight percentiles for gestational age in Taiwan in 2008–2017. Pediatrics & Neonatology. 67(2). 133–138. 1 indexed citations

Kuo, Chun‐Heng, Ming‐Wei Lin, Szu‐Chieh Chen, et al.. (2025). The Effect of Midpregnancy Screening for Gestational Diabetes Mellitus on Pregnancy Outcomes: The TESGO Randomized Controlled Trial. Diabetes Care. 49(3). 384–392. 1 indexed citations

He, Chih‐Tsueng, et al.. (2025). Association between gamma-glutamyl transferase and diabetes factors among elderly nonobese individuals. Medicine. 104(12). e41913–e41913.

Pei, Dee, et al.. (2025). Using machine learning to predict estimated glomerular filtration rate in type 2 diabetes patients: A 4 year-follow-up study. Medicine. 104(40). e44732–e44732.

Chang, Ching‐Yao, et al.. (2024). The risk factors determined by four machine learning methods for the change of difference of bone mineral density in post-menopausal women after three years follow-up. Scientific Reports. 14(1). 23234–23234. 1 indexed citations

Fan, Kang‐Chih, Szu‐Chi Chen, Chun‐Heng Kuo, et al.. (2024). Plasma Angiopoietin-like Protein 4 as a Novel Biomarker Predicting 10-year Mortality in a Community-based Population: A Longitudinal Cohort Study. Archives of Medical Science. 21(1). 51–59.

Kuo, Chun‐Heng, Shu‐Huei Wang, Szu‐Chi Chen, et al.. (2024). Angiopoietin‐like protein 4 induces growth hormone variant secretion and aggravates insulin resistance during pregnancy, linking obesity to gestational diabetes mellitus. BioFactors. 50(6). 1176–1191. 1 indexed citations

Huang, Li-Ying, et al.. (2024). Comparison of multiple linear regression and machine learning methods in predicting cognitive function in older Chinese type 2 diabetes patients. BMC Neurology. 24(1). 11–11. 6 indexed citations

Wu, Chung‐Ze, et al.. (2023). Using Machine Learning to Predict Abnormal Carotid Intima-Media Thickness in Type 2 Diabetes. Diagnostics. 13(11). 1834–1834. 9 indexed citations

10.

Kuo, Chun‐Heng, Ming‐Wei Lin, Kuan‐Yu Chen, et al.. (2023). Advanced maternal age-related clustering of metabolic abnormalities is associated with risks of adverse pregnancy outcomes. Journal of the Formosan Medical Association. 123(3). 325–330. 2 indexed citations

11.

Chen, Fang-Yu, et al.. (2023). Aging Affects Insulin Resistance, Insulin Secretion, and Glucose Effectiveness in Subjects with Normal Blood Glucose and Body Weight. Diagnostics. 13(13). 2158–2158. 8 indexed citations

12.

Huang, Li-Ying, Fang-Yu Chen, Chun‐Heng Kuo, et al.. (2022). Comparing Multiple Linear Regression and Machine Learning in Predicting Diabetic Urine Albumin–Creatinine Ratio in a 4-Year Follow-Up Study. Journal of Clinical Medicine. 11(13). 3661–3661. 11 indexed citations

13.

Chen, Szu‐Chieh, Chien‐Nan Lee, Fu‐Chang Hu, et al.. (2022). Gestational hypertriglyceridemia and adverse pregnancy outcomes: A search for cutoffs using generalized additive models. Diabetes Research and Clinical Practice. 186. 109820–109820. 6 indexed citations

14.

Lin, Jiunn‐Diann, Dee Pei, Chung‐Ze Wu, et al.. (2022). Comparison between Machine Learning and Multiple Linear Regression to Identify Abnormal Thallium Myocardial Perfusion Scan in Chinese Type 2 Diabetes. Diagnostics. 12(7). 1619–1619. 3 indexed citations

15.

Lee, Chien‐Nan, Chun‐Heng Kuo, Ming‐Wei Lin, et al.. (2020). Simplifying the screening of gestational diabetes by maternal age plus fasting plasma glucose at first prenatal visit: A prospective cohort study. PLoS ONE. 15(8). e0237224–e0237224. 9 indexed citations

16.

Lee, Chien‐Nan, Ming‐Wei Lin, Kang‐Chih Fan, et al.. (2019). Overweight and obesity are associated with clustering of metabolic risk factors in early pregnancy and the risk of GDM. PLoS ONE. 14(12). e0225978–e0225978. 56 indexed citations

17.

Kuo, Chun‐Heng & Hung‐Yuan Li. (2019). Diagnostic Strategies for Gestational Diabetes Mellitus: Review of Current Evidence. Current Diabetes Reports. 19(12). 155–155. 17 indexed citations

18.

Wu, Hung‐Tsung, Szu‐Chi Chen, Kang‐Chih Fan, et al.. (2019). Targeting fibrinogen‐like protein 1 is a novel therapeutic strategy to combat obesity. The FASEB Journal. 34(2). 2958–2967. 30 indexed citations

19.

Yu, Tse‐Ya, Jung‐Nan Wei, Chun‐Heng Kuo, et al.. (2017). The Impact of Gastric Atrophy on the Incidence of Diabetes. Scientific Reports. 7(1). 39777–39777. 15 indexed citations

20.

Kuo, Chun‐Heng, Szu‐Chi Chen, Chi‐Tai Fang, et al.. (2017). Screening gestational diabetes mellitus: The role of maternal age. PLoS ONE. 12(3). e0173049–e0173049. 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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