Mai Elezaby

15 papers receiving 229 citations

Peers

Mai Elezaby
Comparison fields: 5 of 49
  • Radiology, Nuclear Medicine and Imaging 115
  • Oncology 66
  • Artificial Intelligence 63
  • Pathology and Forensic Medicine 55
  • Pulmonary and Respiratory Medicine 48
Replace Latifa Fellah with:
Latifa Fellah Belgium
Pål Suhrke Norway
Sana Parsian United States
Gek Kwan-Lim United Kingdom
Luciana Graziano Brazil
Julia Camps Herrero Spain
Zoe Guan United States
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Eric Walk United States
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Mai Elezaby relative to Latifa Fellah Belgium Latifa Fellah's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mai Elezaby

Since Specialization
Citations

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

Fields of papers citing papers by Mai Elezaby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mai Elezaby

This figure shows the co-authorship network connecting the top 25 collaborators of Mai Elezaby. A scholar is included among the top collaborators of Mai Elezaby based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mai Elezaby. Mai Elezaby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 0
2 1
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6 14
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9 31
10 19
11 4
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13 49
14 43
15 35
16
Leveraging Expert Knowledge to Improve Machine-Learned Decision Support Systems.
9
17 10
18 3

About Mai Elezaby

Mai Elezaby is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine and Oncology, having authored 18 papers that have together received 233 indexed citations. Recurring topics across this work include Global Cancer Incidence and Screening (7 papers), AI in cancer detection (6 papers) and Breast Lesions and Carcinomas (6 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (115 citations), Pathology and Forensic Medicine (55 citations) and Cancer Research (41 citations). Mai Elezaby has collaborated with scholars based in United States and Portugal. Frequent co-authors include Elizabeth S. Burnside, Wendy B. DeMartini, Roberta M. Strigel, Amy M. Fowler, Lonie R. Salkowski, Frederick Kelcz, Geng Li, Mythreyi Bhargavan, Ryan W. Woods and Elizabeth A. Sadowski. Their work appears in journals such as PLoS ONE, Radiology and American Journal of Roentgenology.

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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