Rahil Garnavi

3.7k citations
52 papers · 1.4k · h-index 20

Impact in

Papers in

Rahil Garnavi

52 papers receiving 1.4k citations

Peers

Rahil Garnavi
Comparison fields: 5 of 97
  • Ophthalmology 319
  • Radiology, Nuclear Medicine and Imaging 558
  • Computer Vision and Pattern Recognition 454
  • Oncology 564
  • Biophysics 90
Replace Lei Bi with:
Lei Bi Australia
Irene Fondón Spain
Dehui Xiang China
Balázs Harangi Hungary
Weifang Zhu China
Yuhui Ma China
Adrián Colomer Spain
Qiangguo Jin China
Sertan Serte Cyprus
John Arévalo Colombia
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Citations per field
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Citations per year

Countries citing papers authored by Rahil Garnavi

Since Specialization
Citations

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

Fields of papers citing papers by Rahil Garnavi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018181
2 2012136
3 2019134
4 2010124
5 201896
6 201878
7 201662
8 201151
9 201744
10 202043
11 201739
12 202033
13 201630
14 201725
15 201822
16 201522
17 201821
18 201621
19 201721
20 200519

About Rahil Garnavi

Rahil Garnavi is a scholar working on Oncology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Ophthalmology, having authored 52 papers that have together received 1.4k indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (21 papers), AI in cancer detection (14 papers), Retinal Imaging and Analysis (14 papers), Digital Imaging for Blood Diseases (10 papers), Optical Coherence Tomography Applications (8 papers), melanin and skin pigmentation (8 papers), Glaucoma and retinal disorders (7 papers) and Medical Image Segmentation Techniques (7 papers). The work is most often cited by research in Ophthalmology (319 citations), Radiology, Nuclear Medicine and Imaging (558 citations), Computer Vision and Pattern Recognition (454 citations), Oncology (564 citations) and Biophysics (90 citations). Rahil Garnavi has collaborated with scholars based in Australia, United States and Iran. Frequent co-authors include M. Aldeen, Dwarikanath Mahapatra, Behzad Bozorgtabar, Bhavna Antony, Suman Sedai, James Bailey, Gadi Wollstein, Joel S. Schuman, Hiroshi Ishikawa and Yasmeen George. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, IBM Journal of Research and Development, Computerized Medical Imaging and Graphics, Ophthalmology Glaucoma and PLoS ONE.

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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