Mena Gaed

28 papers receiving 381 citations

Peers

Mena Gaed
Comparison fields: 5 of 55
  • Health Informatics 14
  • Radiology, Nuclear Medicine and Imaging 188
  • Artificial Intelligence 208
  • Biophysics 35
  • Pulmonary and Respiratory Medicine 184
Replace Diksha Sharma with:
Diksha Sharma United States
Maysam Shahedi United States
Oscar A. Debats Netherlands
Simon John Christoph Soerensen United States
Farhad Ghazvinian Zanjani Netherlands
Qikui Zhu China
Reza Farjam United States
Kohei Murao Japan
Qianye Yang United Kingdom
T. Whyntie United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Mena Gaed

Since Specialization
Citations

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

Fields of papers citing papers by Mena Gaed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201394
2 201255
3 201533
4 202031
5 201630
6 201328
7 201316
8 201516
9 201311
10 201810
11 20209
12 20158
13 20227
14 20215
15 20205
16 20185
17 20174
18 20134
19 20144
20 20164

About Mena Gaed

Mena Gaed is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 31 papers that have together received 390 indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (22 papers), AI in cancer detection (16 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Prostate Cancer Treatment and Research (8 papers), MRI in cancer diagnosis (6 papers), Medical Imaging and Analysis (5 papers), Medical Image Segmentation Techniques (4 papers) and Spectroscopy and Chemometric Analyses (3 papers). The work is most often cited by research in Health Informatics (14 citations), Radiology, Nuclear Medicine and Imaging (188 citations), Artificial Intelligence (208 citations), Biophysics (35 citations) and Pulmonary and Respiratory Medicine (184 citations). Mena Gaed has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include José A. Gómez, Aaron D. Ward, Madeleine Moussa, Glenn Bauman, Joseph L. Chin, Eli Gibson, Aaron Fenster, Stephen E. Pautler, Aaron Fenster and Olga Veksler. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Journal of Magnetic Resonance Imaging, IEEE Transactions on Biomedical Engineering, IEEE Transactions on Medical Imaging and Medical Physics.

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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