Ibrahim Salama

1.5k citations
51 papers · 404 · h-index 12

Impact in

    • Advanced Statistical Methods and Models
    • Statistical Methods and Bayesian Inference
    • Statistical Methods in Clinical Trials
    • Liver Disease and Transplantation

Papers in

Ibrahim Salama

45 papers receiving 362 citations

Peers

Ibrahim Salama
Comparison fields: 5 of 104
  • Statistics and Probability 90
  • Hepatology 34
  • Management Science and Operations Research 60
  • Mathematical Physics 39
  • Demography 36
Replace John T. Chen with:
John T. Chen United States
J. C. Wakefield United Kingdom
J. D. Kalbfleisch United States
Mario Ouwens United Kingdom
Mark Finkelstein United States
Henrik Ramlau-Hansen Denmark
Ingeborg Waernbaum Sweden
Ahmed H. Abdellah Egypt
Kaushik I. Amin United States
Cheryl L. Faucett United States
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Citations per field
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Citations per year

Countries citing papers authored by Ibrahim Salama

Since Specialization
Citations

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

Fields of papers citing papers by Ibrahim Salama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198349
2 201340
3 197831
4 202020
5 198219
6 200718
7 200318
8 202316
9 201813
10 201312
11 200612
12 201311
13 200711
14 201410
15 19899
16 20019
17 19658
18 20167
19 19837
20 19817

About Ibrahim Salama

Ibrahim Salama is a scholar working on Statistics and Probability, Surgery, Sociology and Political Science, Management Science and Operations Research and Artificial Intelligence, having authored 51 papers that have together received 404 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (6 papers), Advanced Statistical Methods and Models (6 papers), Bayesian Methods and Mixture Models (5 papers), Liver Disease Diagnosis and Treatment (4 papers), Organ Transplantation Techniques and Outcomes (3 papers), Statistical Methods and Inference (3 papers), International Law and Human Rights (3 papers) and Game Theory and Voting Systems (3 papers). The work is most often cited by research in Statistics and Probability (90 citations), Hepatology (34 citations), Management Science and Operations Research (60 citations), Mathematical Physics (39 citations) and Demography (36 citations). Ibrahim Salama has collaborated with scholars based in United States, Egypt and Switzerland. Frequent co-authors include Dana Quade, Mohamed Houseni, Karl Petersen, Gary G. Koch, Dennis H. Tolley, Bernard Greenberg, Halliman H. Winsborough, Carl Yoshizawa, Lawrence L. Kupper and Anastasia Ivanova. Their work appears in journals such as Journal of Laparoendoscopic & Advanced Surgical Techniques, Theoretical Computer Science, Statistics in Medicine, Stochastics and Dynamics and HPB Surgery.

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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