Haitham Elmarakeby
- Molecular Biology
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Oncology
- Pulmonary and Respiratory Medicine
- Co-authors
- Eliezer M. Van AllenKenneth L. KehlDeborah SchragEric KofmanJake R. ConwayShirley MoLenwood S. HeathEva M. Lepisto
- Topics
- Radiomics and Machine Learning in Medical Imaging (5 papers)Cancer Genomics and Diagnostics (5 papers)Lung Cancer Treatments and Mutations (3 papers)
- Journals
- NatureJAMANature Communications
- Partner nations
- United StatesEgyptSaudi Arabia
In The Last Decade
Haitham Elmarakeby
17 papers receiving 744 citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Molecular Biology 301
- Artificial Intelligence 195
- Radiology, Nuclear Medicine and Imaging 159
- Oncology 130
- Pulmonary and Respiratory Medicine 129
Countries citing papers authored by Haitham Elmarakeby
This map shows the geographic impact of Haitham Elmarakeby'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 Haitham Elmarakeby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haitham Elmarakeby more than expected).
Fields of papers citing papers by Haitham Elmarakeby
This network shows the impact of papers produced by Haitham Elmarakeby. 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 Haitham Elmarakeby. The network helps show where Haitham Elmarakeby may publish in the future.
Co-authorship network of co-authors of Haitham Elmarakeby
This figure shows the co-authorship network connecting the top 25 collaborators of Haitham Elmarakeby. A scholar is included among the top collaborators of Haitham Elmarakeby 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 Haitham Elmarakeby. Haitham Elmarakeby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 12 | |
| 3 | 22 | |
| 4 | 33 | |
| 5 | Biologically informed deep neural network for prostate cancer discoverybreakdown → | 239 |
| 6 | 15 | |
| 7 | 24 | |
| 8 | 63 | |
| 9 | 3 | |
| 10 | 97 | |
| 11 | 113 | |
| 12 | 1 | |
| 13 | 37 | |
| 14 | 23 | |
| 15 | 8 | |
| 16 | 54 | |
| 17 | 1 |
About Haitham Elmarakeby
Haitham Elmarakeby is a scholar working on Cancer Research, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 753 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Cancer Genomics and Diagnostics (5 papers) and Lung Cancer Treatments and Mutations (3 papers). The work is most often cited by research in Health Informatics (65 citations), Cancer Research (125 citations) and Radiology, Nuclear Medicine and Imaging (159 citations). Haitham Elmarakeby has collaborated with scholars based in United States, Egypt and Saudi Arabia. Frequent co-authors include Eliezer M. Van Allen, Kenneth L. Kehl, Deborah Schrag, Eric Kofman, Jake R. Conway, Shirley Mo, Lenwood S. Heath, Eva M. Lepisto, Michael J. Hassett and Bruce E. Johnson. Their work appears in journals such as Nature, JAMA and Nature Communications.
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.