Ihab R. Kamel

27.3k citations
413 papers · 17.6k indexed · 5 hit papers · h-index 69
Topics
Hepatocellular Carcinoma Treatment and Prognosis (131 papers)MRI in cancer diagnosis (101 papers)Radiomics and Machine Learning in Medical Imaging (69 papers)
Journals
New England Journal of MedicineJournal of Clinical OncologySHILAP Revista de lepidopterología

In The Last Decade

Ihab R. Kamel

396 papers receiving 17.3k citations

Hit Papers

Diagnostic accuracy and reliability of ultrasonography fo...2011202620162021201120132012202320162505007501000

Peers

Ihab R. Kamel
Comparison fields: 5 of 172
  • Surgery 5.5k
  • Hepatology 5.1k
  • Epidemiology 5.1k
  • Radiology, Nuclear Medicine and Imaging 4.6k
  • Oncology 4.0k
Replace Jan N.M. IJzermans with:
Jan N.M. IJzermans Netherlands
Ken Shirabe Japan
Pierre–Alain Clavien Switzerland
Mitsuo Shimada Japan
Norihiro Kokudo Japan
Richard D. Schulick United States
Paris Tekkis United Kingdom
T. Peter Kingham United States
Daniel Azoulay France
Christopher L. Wolfgang United States
Ihab R. Kamel relative to Jan N.M. IJzermans Netherlands Jan N.M. IJzermans's profile →
Citations per field
00.5×5.2×
Jan N.M. IJzermans · 1×
Citations per year

Countries citing papers authored by Ihab R. Kamel

Since Specialization
Citations

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

Fields of papers citing papers by Ihab R. Kamel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ihab R. Kamel. 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 Ihab R. Kamel. The network helps show where Ihab R. Kamel may publish in the future.

Co-authorship network of co-authors of Ihab R. Kamel

This figure shows the co-authorship network connecting the top 25 collaborators of Ihab R. Kamel. A scholar is included among the top collaborators of Ihab R. Kamel 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 Ihab R. Kamel. Ihab R. Kamel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 0
4 0
5 3
6 39
7 0
8 4
9 1
10 3
11 4
12 13
13 11
14 7
15 83
16 119
17 247
18 304
19 338
20 33

About Ihab R. Kamel

Ihab R. Kamel is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging and Oncology, having authored 413 papers that have together received 17.6k indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (131 papers), MRI in cancer diagnosis (101 papers) and Radiomics and Machine Learning in Medical Imaging (69 papers). The work is most often cited by research in Hepatology (5.1k citations), Radiology, Nuclear Medicine and Imaging (4.6k citations) and Epidemiology (5.1k citations). Ihab R. Kamel has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Susanne Bonekamp, David A. Bluemke, Timothy M. Pawlik, Jean-François H. Geschwind, Jeanne M. Clark, Mariana Lazo, Rubén Hernáez, Eliseo Güallar, Frederick L. Brancati and Katarzyna J. Macura. Their work appears in journals such as New England Journal of Medicine, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

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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