David X. Jin

472 citations
33 papers · 322 · h-index 9

Impact in

    • Pancreatitis Pathology and Treatment
    • Bariatric Surgery and Outcomes
    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 and COVID-19 Research

Papers in

    • Pancreatitis Pathology and Treatment 17
    • Gastrointestinal disorders and treatments 2
    • Pancreatic and Hepatic Oncology Research 6
    • Inflammatory Biomarkers in Disease Prognosis 3

David X. Jin

32 papers receiving 321 citations

Peers

David X. Jin
Comparison fields: 5 of 43
  • Surgery 184
  • Infectious Diseases 73
  • Oncology 71
  • Geriatrics and Gerontology 8
  • Neurology 26
Replace Nuri Alper Şahbaz with:
Nuri Alper Şahbaz Türkiye
Burak İlhan Türkiye
Luís CU Nakano Brazil
Houssam Bkiyar Morocco
Ramazan Asoğlu Türkiye
Ígor Mendonça Proença Brazil
Victor Bilman Italy
J P Marmuse France
Derya Gökçınar Türkiye
Chau To United States
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Citations per field
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Citations per year

Countries citing papers authored by David X. Jin

Since Specialization
Citations

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

Fields of papers citing papers by David X. Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David X. Jin. 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 David X. Jin. The network helps show where David X. Jin may publish in the future.

Co-authors

The 25 scholars most cited alongside David X. Jin, 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 David X. Jin Line = papers co-authored together David X. Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202079
2 201772
3 202118
4 202118
5 202017
6 202113
7 201911
8 201711
9 20159
10 20238
11 20198
12 20197
13 20186
14 20195
15 20205
16 20215
17 20224
18 20194
19 20204
20 20233

About David X. Jin

David X. Jin is a scholar working on Surgery, Oncology, Cardiology and Cardiovascular Medicine, Epidemiology and Infectious Diseases, having authored 33 papers that have together received 322 indexed citations. Recurring topics across this work include Pancreatitis Pathology and Treatment (17 papers), Pancreatic and Hepatic Oncology Research (6 papers), Inflammatory Biomarkers in Disease Prognosis (3 papers), Gastrointestinal disorders and treatments (2 papers), Acute Myocardial Infarction Research (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Cardiac, Anesthesia and Surgical Outcomes (1 paper) and Diabetes Management and Research (1 paper). The work is most often cited by research in Surgery (184 citations), Infectious Diseases (73 citations), Oncology (71 citations), Geriatrics and Gerontology (8 citations) and Neurology (26 citations). David X. Jin has collaborated with scholars based in United States, Australia and Italy. Frequent co-authors include Julia McNabb‐Baltar, Taha Qazi, Pichamol Jirapinyo, Nitin Mishra, Christopher C. Thompson, Peter A. Banks, Thomas R. McCarty, Walker D. Redd, Joyce Zhou and Kelly Hathorn. Their work appears in journals such as Gastroenterology, Digestive Diseases and Sciences, Pancreas, Pancreatology and Gastrointestinal Endoscopy.

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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