Chen Dun

49 papers receiving 579 citations

Chen Dun's Hit Papers

Current progress and open challenges for applying deep learning across the biosciences 2022 · 202 citations
2020+1+2Years since publication50100150200

Peers

Chen Dun
Comparison fields: 5 of 104
  • Ophthalmology 60
  • Health Informatics 6
  • Internal Medicine 11
  • Surgery 135
  • Public Health, Environmental and Occupational Health 58
Replace Raymond Liu with:
Raymond Liu United States
Konstantinos Oikonomou Greece
Weng Onn Chan Australia
Hyun Wook Han South Korea
Sheng Zhou China
Kathie Godfrey United Kingdom
Lance A. Williams United States
Andrew R. Miller United States
Fabio Longo Italy
Joseph R. Martel United States
Chen Dun relative to Raymond Liu United States Raymond Liu's profile →
Citations per field
00.5×6.2×
Raymond Liu · 1×
Citations per year

Countries citing papers authored by Chen Dun

Since Specialization
Citations

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

Fields of papers citing papers by Chen Dun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Current progress and open challenges for applying deep learning across the biosciences
Hit paper breakdown →
2022202
2 202246
3 202145
4 202130
5 202227
6 202023
7 202223
8 202221
9 202117
10 202216
11 202315
12 202210
13 202310
14 20249
15 20218
16 20236
17 20246
18 20226
19 20235
20 20235

About Chen Dun

Chen Dun is a scholar working on Surgery, Ophthalmology, Pulmonary and Respiratory Medicine, General Health Professions and Artificial Intelligence, having authored 63 papers that have together received 591 indexed citations. Recurring topics across this work include Peripheral Artery Disease Management (22 papers), Ocular Infections and Treatments (8 papers), Vascular Procedures and Complications (5 papers), Venous Thromboembolism Diagnosis and Management (3 papers), Corneal surgery and disorders (3 papers), Patient Satisfaction in Healthcare (2 papers), Renal and Vascular Pathologies (2 papers) and Intraocular Surgery and Lenses (2 papers). The work is most often cited by research in Ophthalmology (60 citations), Health Informatics (6 citations), Internal Medicine (11 citations), Surgery (135 citations) and Public Health, Environmental and Occupational Health (58 citations). Chen Dun has collaborated with scholars based in United States, Germany and Singapore. Frequent co-authors include Martin A. Makary, Caitlin W. Hicks, James H. Black, Anastasios Kyrillidis, Fasika A. Woreta, C. Wolfe, Christopher J. Abularrage, Christi Walsh, Richard G. Baraniuk and Todd J. Treangen. Their work appears in journals such as Journal of Vascular Surgery, Ophthalmology, Annals of Vascular Surgery, Cornea and Journal of Cataract & Refractive Surgery.

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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