Daniel Jin

857 citations
20 papers · 623 · h-index 11

Impact in

    • Mesenchymal stem cell research
    • Tissue Engineering and Regenerative Medicine
    • Thyroid and Parathyroid Surgery

Papers in

    • Spinal Fractures and Fixation Techniques 2
    • Tissue Engineering and Regenerative Medicine 2
    • Renal and related cancers 4

Daniel Jin

19 papers receiving 595 citations

Peers

Daniel Jin
Comparison fields: 5 of 90
  • Genetics 66
  • Surgery 228
  • Pulmonary and Respiratory Medicine 136
  • Radiology, Nuclear Medicine and Imaging 64
  • Obstetrics and Gynecology 20
Replace Giuseppe Salvaggio with:
Giuseppe Salvaggio Italy
Ning Lang China
James Szymanski United States
Yongyan Gao China
Glenn A. Rouse United States
Kensaku Mori Japan
Ali Akhavan Iran
Fumi Kato Japan
Romain Gillet France
Sang Yub Lee South Korea
Daniel Jin relative to Giuseppe Salvaggio Italy Giuseppe Salvaggio's profile →
Citations per field
00.5×3.3×
Giuseppe Salvaggio · 1×
Citations per year

Countries citing papers authored by Daniel Jin

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2007163
2 2008129
3 202382
4 200960
5 201045
6 201131
7 201125
8 200724
9 202022
10 200911
11 202011
12 20228
13 20225
14 20212
15 20241
16 20231
17 20051
18 20051
19 20091
20 20250

About Daniel Jin

Daniel Jin is a scholar working on Surgery, Molecular Biology, Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine and Artificial Intelligence, having authored 20 papers that have together received 623 indexed citations. Recurring topics across this work include Renal and related cancers (4 papers), Kidney Stones and Urolithiasis Treatments (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Organ Donation and Transplantation (2 papers), Renal and Vascular Pathologies (2 papers), Spinal Fractures and Fixation Techniques (2 papers), Tissue Engineering and Regenerative Medicine (2 papers) and Head and Neck Cancer Studies (1 paper). The work is most often cited by research in Genetics (66 citations), Surgery (228 citations), Pulmonary and Respiratory Medicine (136 citations), Radiology, Nuclear Medicine and Imaging (64 citations) and Obstetrics and Gynecology (20 citations). Daniel Jin has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include D. Duane Baldwin, Forrest Jellison, Ryan S. Hsi, Laura Perin, Sargis Sedrakyan, Stefano Giuliani, David Warburton, Gianni Carraro, Anthony Atala and Roger E. De Filippo. Their work appears in journals such as The Journal of Urology, Journal of the American College of Surgeons, Journal of Endourology, Journal of Neurotrauma and Cell Proliferation.

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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