Hesham Eldaly
Impact in
- Artificial Intelligence top 5%
- AI in cancer detection
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
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- Lymphoma Diagnosis and Treatment 5
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- AI in cancer detection 6
- Co-authors
- Nasir Rajpoot (4 shared papers)Adnan Mujahid Khan (2 shared papers)Miriam Kull (1 shared paper)Milena Pantić (1 shared paper)Uwe M. Martens (1 shared paper)Cornelius Florian Waller (1 shared paper)Stefan Zimmermann (1 shared paper)Thomas W. J. Lennard (1 shared paper)
- Journals
- Nature Communications (2 papers)European Journal Of Haematology (2 papers)Journal of Pathology Informatics (2 papers)British Journal of Haematology (2 papers)Blood (1 paper)
- Partner nations
- United KingdomEgyptNetherlands
In The Last Decade
Hesham Eldaly
25 papers receiving 905 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 379
- Health Informatics 20
- Pathology and Forensic Medicine 88
- Physiology 107
- Internal Medicine 12
Countries citing papers authored by Hesham Eldaly
This map shows the geographic impact of Hesham Eldaly'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 Hesham Eldaly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hesham Eldaly more than expected).
Fields of papers citing papers by Hesham Eldaly
This network shows the impact of papers produced by Hesham Eldaly. 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 Hesham Eldaly. The network helps show where Hesham Eldaly may publish in the future.
Co-authors
The 25 scholars most cited alongside Hesham Eldaly, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 198 | |
| 2 | 2004 | 129 | |
| 3 | 2013 | 94 | |
| 4 | 2009 | 81 | |
| 5 | 2007 | 74 | |
| 6 | 2019 | 55 | |
| 7 | 2013 | 44 | |
| 8 | 2022 | 41 | |
| 9 | 2017 | 36 | |
| 10 | 2021 | 30 | |
| 11 | 2023 | 25 | |
| 12 | 2023 | 21 | |
| 13 | 2024 | 20 | |
| 14 | 2012 | 15 | |
| 15 | 2017 | 12 | |
| 16 | 2009 | 11 | |
| 17 | 2010 | 10 | |
| 18 | 2007 | 8 | |
| 19 | 2023 | 5 | |
| 20 | 2012 | 4 |
About Hesham Eldaly
Hesham Eldaly is a scholar working on Pathology and Forensic Medicine, Artificial Intelligence, Hematology, Oncology and Otorhinolaryngology, having authored 26 papers that have together received 925 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Lymphoma Diagnosis and Treatment (5 papers), Viral-associated cancers and disorders (2 papers), Adrenal and Paraganglionic Tumors (1 paper), Case Reports on Hematomas (1 paper), Ocular Oncology and Treatments (1 paper), Acute Myeloid Leukemia Research (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Artificial Intelligence (379 citations), Health Informatics (20 citations), Pathology and Forensic Medicine (88 citations), Physiology (107 citations) and Internal Medicine (12 citations). Hesham Eldaly has collaborated with scholars based in United Kingdom, Egypt and Netherlands. Frequent co-authors include Nasir Rajpoot, Adnan Mujahid Khan, Miriam Kull, Milena Pantić, Uwe M. Martens, Cornelius Florian Waller, Stefan Zimmermann, Thomas W. J. Lennard, Simi Ali and John Andrew Kirby. Their work appears in journals such as Nature Communications, European Journal Of Haematology, Journal of Pathology Informatics, British Journal of Haematology and Blood.
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.