Eric J. Kuo

1.1k citations
31 papers · 782 · h-index 13

Impact in

Papers in

Eric J. Kuo

31 papers receiving 770 citations

Peers

Eric J. Kuo
Comparison fields: 5 of 37
  • Endocrinology, Diabetes and Metabolism 386
  • Nephrology 127
  • Oncology 148
  • Epidemiology 179
  • Anatomy 7
Replace Laurence Leclerc with:
Laurence Leclerc France
Kenneth E. Levin United States
Kiyomi Horiuchi Japan
Peter Czako United States
Jorge Rosa Santos Portugal
Amanda N. Graff‐Baker United States
D B Calandra United States
John M. Monchik United States
Steven A. De Jong United States
Rajeev Kasaliwal India
Eric J. Kuo relative to Laurence Leclerc France Laurence Leclerc's profile →
Citations per field
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Laurence Leclerc · 1×
Citations per year

Countries citing papers authored by Eric J. Kuo

Since Specialization
Citations

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

Fields of papers citing papers by Eric J. Kuo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric J. 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 Eric J. Kuo. The network helps show where Eric J. Kuo may publish in the future.

Co-authors

The 25 scholars most cited alongside Eric J. Kuo, 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 Eric J. Kuo Line = papers co-authored together Eric J. Kuo 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 2013168
2 2020118
3 201368
4 201766
5 201854
6 201344
7 201840
8 201838
9 201728
10 201728
11 201719
12 201417
13 201812
14 202411
15 201711
16 20229
17 20178
18 20227
19 20226
20 20196

About Eric J. Kuo

Eric J. Kuo is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Nephrology, Oncology and Epidemiology, having authored 31 papers that have together received 782 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (17 papers), Parathyroid Disorders and Treatments (5 papers), Adrenal and Paraganglionic Tumors (4 papers), Pancreatic and Hepatic Oncology Research (2 papers), BRCA gene mutations in cancer (2 papers), Neuroendocrine Tumor Research Advances (2 papers), Pancreatitis Pathology and Treatment (2 papers) and Electrolyte and hormonal disorders (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (386 citations), Nephrology (127 citations), Oncology (148 citations), Epidemiology (179 citations) and Anatomy (7 citations). Eric J. Kuo has collaborated with scholars based in United States, Italy and South Korea. Frequent co-authors include Ronald R. Salem, Michael W. Yeh, Masha J. Livhits, Sanziana A. Roman, Julie Ann Sosa, Kyle Zanocco, Ning Li, Paolo Goffredo, Shonan Sho and Angela M. Leung. Their work appears in journals such as Surgery, Thyroid, Endocrine Practice, The American Journal of Surgery and Annals of Surgical Oncology.

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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