Dan Ruan

4.4k citations
196 papers · 3.3k · h-index 32

Impact in

Papers in

Dan Ruan

181 papers receiving 3.3k citations

Peers

Dan Ruan
Comparison fields: 5 of 130
  • Radiation 1.6k
  • Radiology, Nuclear Medicine and Imaging 1.1k
  • Pulmonary and Respiratory Medicine 918
  • Health Informatics 32
  • Computer Vision and Pattern Recognition 255
Replace Pretesh Patel with:
Pretesh Patel United States
Annette Haworth Australia
Simon Doran United Kingdom
Marc L. Kessler United States
Carri Glide‐Hurst United States
Lois Holloway Australia
Ke Sheng United States
Indrin J. Chetty United States
Weiguo Lu United States
Christoph Bert Germany
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Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Dan Ruan

Since Specialization
Citations

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

Fields of papers citing papers by Dan Ruan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 196 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020179
2 2018158
3 2012140
4 2013117
5 202080
6 201977
7 202075
8 201067
9 201059
10 200759
11 201059
12 201858
13 200856
14 201855
15 200955
16 201554
17 201754
18 201054
19 201453
20 201849

About Dan Ruan

Dan Ruan is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 196 papers that have together received 3.3k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (82 papers), Medical Imaging Techniques and Applications (32 papers), Medical Image Segmentation Techniques (22 papers), Radiation Therapy and Dosimetry (18 papers), Advanced MRI Techniques and Applications (18 papers), Advanced X-ray and CT Imaging (11 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Medical Imaging and Analysis (8 papers). The work is most often cited by research in Radiation (1.6k citations), Radiology, Nuclear Medicine and Imaging (1.1k citations), Pulmonary and Respiratory Medicine (918 citations), Health Informatics (32 citations) and Computer Vision and Pattern Recognition (255 citations). Dan Ruan has collaborated with scholars based in United States, China and Denmark. Frequent co-authors include Ke Sheng, Paul Keall, Daniel A. Low, Jeffrey A. Fessler, James M. Balter, Amit Sawant, Yingli Yang, Byungchul Cho, P.R. Poulsen and Daniel O’Connor. Their work appears in journals such as Medical Physics, International Journal of Radiation Oncology*Biology*Physics, Physics in Medicine and Biology, Frontiers in Oncology and Journal of Magnetic Resonance Imaging.

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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