Jun Tan

849 citations
50 papers · 601 · h-index 12

Impact in

Papers in

Jun Tan

44 papers receiving 582 citations

Peers

Jun Tan
Comparison fields: 5 of 68
  • Radiation 308
  • Health Informatics 14
  • Radiology, Nuclear Medicine and Imaging 231
  • Otorhinolaryngology 21
  • Computer Networks and Communications 99
Replace Belal Ahmad with:
Belal Ahmad Canada
Yulong Yan United States
Zhiguo Zhou China
Chenyang Shen United States
Azar Sadeghnejad Barkousaraie United States
José Marcio Luna United States
William C. Sleeman United States
Eric Schnarr United States
Wu Liu China
Jun Tan relative to Belal Ahmad Canada Belal Ahmad's profile →
Citations per field
00.5×5.8×
Belal Ahmad · 1×
Citations per year

Countries citing papers authored by Jun Tan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015111
2 201593
3 201888
4 201540
5 200328
6 201725
7 200520
8 201718
9 200616
10 200914
11 202412
12 201412
13 200511
14 201410
15 201210
16 20229
17 20158
18 20078
19 20146
20 20215

About Jun Tan

Jun Tan is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 50 papers that have together received 601 indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (19 papers), Medical Imaging Techniques and Applications (8 papers), Wireless Communication Networks Research (7 papers), Radiation Dose and Imaging (6 papers), Radiation Therapy and Dosimetry (6 papers), Advanced Wireless Communication Techniques (5 papers), Advanced X-ray and CT Imaging (3 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Radiation (308 citations), Health Informatics (14 citations), Radiology, Nuclear Medicine and Imaging (231 citations), Otorhinolaryngology (21 citations) and Computer Networks and Communications (99 citations). Jun Tan has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Lindsey Olsen, G.L. Stüber, Kevin L. Moore, Satomi Shiraishi, Sasa Mutic, Yang Yu, Shiyong Chen, Qing Da, Jeff M. Michalski and Kevin L. Moore. Their work appears in journals such as Medical Physics, International Journal of Radiation Oncology*Biology*Physics, Physics in Medicine and Biology, Practical Radiation Oncology and Radiology Artificial Intelligence.

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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