Dao‐Ming Chang

1.5k total citations · 1 hit paper
17 papers, 1.2k citations indexed

About

Dao‐Ming Chang is a scholar working on Epidemiology, Physiology and Molecular Biology. According to data from OpenAlex, Dao‐Ming Chang has authored 17 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Epidemiology, 5 papers in Physiology and 4 papers in Molecular Biology. Recurrent topics in Dao‐Ming Chang's work include Adipokines, Inflammation, and Metabolic Diseases (5 papers), Regulation of Appetite and Obesity (3 papers) and Adipose Tissue and Metabolism (3 papers). Dao‐Ming Chang is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (5 papers), Regulation of Appetite and Obesity (3 papers) and Adipose Tissue and Metabolism (3 papers). Dao‐Ming Chang collaborates with scholars based in Taiwan and China. Dao‐Ming Chang's co-authors include Yau‐Jiunn Lee, Shyi‐Jang Shin, Jack C.‐R. Tsai, Fu‐Mei Chung, Yu‐Hung Chang, Sheng‐Hsiung Sheu, Herng‐Chia Chiu, Kun‐Chen Lin, Chang‐Hsun Hsieh and Chen‐Chou Lei and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, Diabetes Care and Sensors.

In The Last Decade

Dao‐Ming Chang

17 papers receiving 1.2k citations

Hit Papers

Elevated Plasma Level of Visfatin/Pre-B Cell Colony-Enhan... 2006 2026 2012 2019 2006 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dao‐Ming Chang Taiwan 10 742 415 234 219 199 17 1.2k
Jack C.‐R. Tsai Taiwan 9 701 0.9× 392 0.9× 220 0.9× 299 1.4× 168 0.8× 12 1.2k
永井 良三 Japan 2 787 1.1× 548 1.3× 269 1.1× 260 1.2× 225 1.1× 2 1.2k
Zdeňka Vernerová Czechia 22 423 0.6× 246 0.6× 94 0.4× 287 1.3× 360 1.8× 56 1.4k
Díez Jj Spain 7 553 0.7× 389 0.9× 228 1.0× 171 0.8× 179 0.9× 18 1.1k
Małgorzata Szelachowska Poland 18 369 0.5× 284 0.7× 78 0.3× 149 0.7× 185 0.9× 90 1.2k
Delphine Bastelica France 13 717 1.0× 413 1.0× 94 0.4× 204 0.9× 349 1.8× 18 1.3k
Tiziana Ronti Italy 6 341 0.5× 317 0.8× 126 0.5× 198 0.9× 126 0.6× 7 822
Flavia Agata Cimini Italy 20 614 0.8× 332 0.8× 70 0.3× 139 0.6× 287 1.4× 55 1.3k
Joanna Janowska Poland 16 427 0.6× 321 0.8× 157 0.7× 234 1.1× 160 0.8× 53 983
Carolin Tonus Germany 9 764 1.0× 537 1.3× 165 0.7× 238 1.1× 214 1.1× 25 1.3k

Countries citing papers authored by Dao‐Ming Chang

Since Specialization
Citations

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

Fields of papers citing papers by Dao‐Ming Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dao‐Ming Chang. 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 Dao‐Ming Chang. The network helps show where Dao‐Ming Chang may publish in the future.

Co-authorship network of co-authors of Dao‐Ming Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Dao‐Ming Chang. A scholar is included among the top collaborators of Dao‐Ming Chang 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 Dao‐Ming Chang. Dao‐Ming Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
2.
Chang, Yu‐Hung, et al.. (2018). Elevated serum cytokeratin-18 concentration in patients with type 2 diabetes mellitus and non-alcoholic fatty liver disease. Annals of Clinical Biochemistry International Journal of Laboratory Medicine. 56(1). 141–147. 16 indexed citations
3.
Lee, Chia‐Wei, et al.. (2018). Escherichia coli Fiber Sensors Using Concentrated Dielectrophoretic Force with Optical Defocusing Method. ACS Sensors. 3(6). 1196–1202. 9 indexed citations
4.
Chang, Yu‐Hung, et al.. (2017). Renal function preservation with pioglitazone or with basal insulin as an add-on therapy for patients with type 2 diabetes mellitus. Acta Diabetologica. 54(6). 561–568. 10 indexed citations
5.
Chang, Dao‐Ming, et al.. (2016). Sensitive Detection of Small Particles in Fluids Using Optical Fiber Tip with Dielectrophoresis. Sensors. 16(3). 303–303. 6 indexed citations
6.
Chang, Yu‐Hung, Chen‐Chou Lei, Kun‐Chen Lin, et al.. (2015). Serum uric acid level as an indicator for CKD regression and progression in patients with type 2 diabetes mellitus—a 4.6‐year cohort study. Diabetes/Metabolism Research and Reviews. 32(6). 557–564. 49 indexed citations
7.
Chang, Yu‐Hung, et al.. (2013). Paradoxical Negative HDL Cholesterol Response to Atorvastatin and Simvastatin Treatment in Chinese Type 2 Diabetic Patients. The Review of Diabetic Studies. 10(2-3). 213–222. 7 indexed citations
8.
Chang, Yu‐Hung, et al.. (2011). Visfatin in overweight/obesity, type 2 diabetes mellitus, insulin resistance, metabolic syndrome and cardiovascular diseases: a meta‐analysis and systemic review. Diabetes/Metabolism Research and Reviews. 27(6). 515–527. 286 indexed citations
9.
Chung, Fu‐Mei, Tien‐Yu Shieh, Yi‐Hsin Yang, et al.. (2007). The role of angiotensin-converting enzyme gene insertion/deletion polymorphism for blood pressure regulation in areca nut chewers. Translational research. 150(1). 58–65. 8 indexed citations
10.
Chung, Fu‐Mei, et al.. (2006). Elevated Plasma Level of Visfatin/Pre-B Cell Colony-Enhancing Factor in Patients with Type 2 Diabetes Mellitus. The Journal of Clinical Endocrinology & Metabolism. 91(1). 295–299. 559 indexed citations breakdown →
11.
Tsai, Jack C.‐R., Sheng‐Hsiung Sheu, Herng‐Chia Chiu, et al.. (2006). Association of peripheral total and differential leukocyte counts with metabolic syndrome and risk of ischemic cardiovascular diseases in patients with type 2 diabetes mellitus. Diabetes/Metabolism Research and Reviews. 23(2). 111–118. 92 indexed citations
13.
Chung, Fu‐Mei, Jack C.‐R. Tsai, Dao‐Ming Chang, Shyi‐Jang Shin, & Yau‐Jiunn Lee. (2005). Peripheral Total and Differential Leukocyte Count in Diabetic Nephropathy. Diabetes Care. 28(7). 1710–1717. 102 indexed citations
14.
Tsai, Jack C.‐R., et al.. (2004). A Case of Acquired Generalized Lipodystrophy with Cerebellar Degeneration and Type 2 Diabetes Mellitus. The Review of Diabetic Studies. 1(4). 193–193. 3 indexed citations
15.
Chang, Dao‐Ming, et al.. (2004). The Association of Silent Coronary Artery Disease and Metabolic Syndrome in Chinese with Type 2 Diabetes Mellitus. The Review of Diabetic Studies. 1(1). 18–18. 5 indexed citations
16.
Lee, Yau‐Jiunn, Dao‐Ming Chang, & Jack C.‐R. Tsai. (2003). Association of a 27-bp repeat polymorphism in intron 4 of endothelial constitutive nitric oxide synthase gene with serum uric acid levels in chinese subjects with type 2 diabetes. Metabolism. 52(11). 1448–1453. 8 indexed citations
17.
Chang, Dao‐Ming, et al.. (2003). Association of Resistin Gene 3′-Untranslated Region +62G→A Polymorphism with Type 2 Diabetes and Hypertension in a Chinese Population. The Journal of Clinical Endocrinology & Metabolism. 88(3). 1258–1263. 60 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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