Ted Wu

1.1k citations
31 papers · 856 · 1 hit paper · h-index 12

Impact in

Papers in

Ted Wu

29 papers receiving 829 citations

Ted Wu's Hit Papers

Long-Term Complications and Mortality in Young-Onset Diabetes 2013 · 329 citations
3290+4+8Years since publication100200300

Peers

Ted Wu
Comparison fields: 5 of 85
  • Endocrinology, Diabetes and Metabolism 365
  • Family Practice 10
  • Drug Discovery 1
  • Nephrology 37
  • Genetics 112
Replace Connie Luo with:
Connie Luo Australia
James J. Chamberlain United States
Wayne Weng United States
Priya M. John United States
Fernando Álvarez Guisasola Spain
Harpreet S. Bajaj Canada
American Diabetes Association
K.M. PRASANNA KUMAR India
SV Madhu India
Ie Byung Park South Korea
Ted Wu relative to Connie Luo Australia Connie Luo's profile →
Citations per field
00.5×1.5×1.8×
Connie Luo · 1×
Citations per year

Countries citing papers authored by Ted Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ted Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ted Wu. 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 Ted Wu. The network helps show where Ted Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Ted Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ted Wu Line = papers co-authored together Ted Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Long-Term Complications and Mortality in Young-Onset Diabetes
Hit paper breakdown →
2013329
2 2016202
3 201534
4 201932
5 202032
6 201731
7 201523
8 200522
9 200921
10 202120
11 202216
12 201712
13 202110
14 202210
15 201410
16 20149
17 20217
18 20227
19 20216
20 20194

About Ted Wu

Ted Wu is a scholar working on Endocrinology, Diabetes and Metabolism, Obstetrics and Gynecology, Nephrology, General Health Professions and Molecular Biology, having authored 31 papers that have together received 856 indexed citations. Recurring topics across this work include Diabetes Management and Research (7 papers), Gestational Diabetes Research and Management (4 papers), Diabetes Treatment and Management (4 papers), Chronic Kidney Disease and Diabetes (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers), Retinal Diseases and Treatments (2 papers), Mobile Health and mHealth Applications (2 papers) and Diabetes Management and Education (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (365 citations), Family Practice (10 citations), Drug Discovery (1 citation), Nephrology (37 citations) and Genetics (112 citations). Ted Wu has collaborated with scholars based in Australia, Saudi Arabia and Canada. Frequent co-authors include Jencia Wong, Stephen M. Twigg, Dennis K. Yue, Lynda Molyneaux, Maria Constantino, Connie Luo, Abdulghani Alsaeed, Mario D’Souza, Timothy Middleton and Margaret McGill. Their work appears in journals such as Journal of Diabetes and its Complications, Diabetes Research and Clinical Practice, Diabetes Care, Diabetes Therapy and Diabetic Medicine.

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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