Ahmed Hosny

16.1k total citations · 7 hit papers
50 papers, 10.1k citations indexed

About

Ahmed Hosny is a scholar working on Radiology, Nuclear Medicine and Imaging, Geophysics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ahmed Hosny has authored 50 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 15 papers in Geophysics and 11 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ahmed Hosny's work include Radiomics and Machine Learning in Medical Imaging (18 papers), earthquake and tectonic studies (12 papers) and Lung Cancer Diagnosis and Treatment (9 papers). Ahmed Hosny is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (18 papers), earthquake and tectonic studies (12 papers) and Lung Cancer Diagnosis and Treatment (9 papers). Ahmed Hosny collaborates with scholars based in United States, Egypt and Netherlands. Ahmed Hosny's co-authors include Hugo J.W.L. Aerts, Chintan Parmar, Lawrence H. Schwartz, John Quackenbush, Steve Pieper, Andriy Fedorov, Joost J. M. van Griethuysen, Jean‐Christophe Fillion‐Robin, Nicole Aucoin and Vivek Narayan and has published in prestigious journals such as Science, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Ahmed Hosny

46 papers receiving 9.9k citations

Hit Papers

Computational Radiomics System to Decode the Radiographic... 2017 2026 2020 2023 2017 2018 2019 2019 2018 1000 2.0k 3.0k 4.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Computational Radiomics System to Decode the Radiographic Phenotype
    2017 4.2k citations Joost J. M. van Griethuysen, Andriy Fedorov et al. Cancer Research profile →
  2. Artificial intelligence in radiology
    2018 2.3k citations Ahmed Hosny, Chintan Parmar et al. Nature reviews. Cancer profile →
  3. Artificial intelligence in cancer imaging: Clinical challenges and applications
    2019 1.2k citations Ahmed Hosny, Nicolai J. Birkbak et al. profile →
  4. Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging
    2019 402 citations Yiwen Xu, Ahmed Hosny et al. Clinical Cancer Research profile →
  5. Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
    2018 398 citations Ahmed Hosny, Chintan Parmar et al. PLoS Medicine profile →
  6. Deep learning classification of lung cancer histology using CT images
    2021 163 citations Tafadzwa L. Chaunzwa, Ahmed Hosny et al. profile →
  7. Foundation model for cancer imaging biomarkers
    2024 63 citations Suraj Pai, Dennis Bontempi et al. Nature Machine Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ahmed Hosny United States 21 7.4k 2.8k 2.3k 2.2k 1.5k 50 10.1k
Jayashree Kalpathy–Cramer United States 41 6.0k 0.8× 2.2k 0.8× 2.2k 1.0× 1.5k 0.7× 817 0.5× 237 12.0k
Bradley J. Erickson United States 49 4.5k 0.6× 1.5k 0.5× 1.4k 0.6× 1.8k 0.8× 1.1k 0.7× 280 10.4k
Chintan Parmar United States 26 13.5k 1.8× 5.4k 2.0× 3.9k 1.7× 3.0k 1.4× 1.4k 0.9× 36 15.8k
Di Dong China 53 7.3k 1.0× 4.0k 1.4× 1.7k 0.7× 1.6k 0.7× 313 0.2× 199 9.5k
Sara Carvalho Netherlands 17 8.9k 1.2× 3.5k 1.3× 2.5k 1.1× 1.5k 0.7× 307 0.2× 37 9.9k
Henry C. Woodruff Netherlands 35 5.5k 0.7× 2.2k 0.8× 1.5k 0.7× 1.1k 0.5× 384 0.3× 104 6.8k
Issam El Naqa United States 59 8.3k 1.1× 6.0k 2.2× 2.4k 1.0× 1.8k 0.8× 530 0.4× 349 14.9k
Wouter van Elmpt Netherlands 44 8.4k 1.1× 4.2k 1.5× 2.5k 1.1× 977 0.4× 352 0.2× 193 10.2k
Namkug Kim South Korea 55 4.6k 0.6× 2.9k 1.1× 1.9k 0.8× 1.2k 0.5× 423 0.3× 412 10.9k
Kyunghwa Han South Korea 42 3.9k 0.5× 1.7k 0.6× 940 0.4× 1.1k 0.5× 619 0.4× 328 8.0k

Countries citing papers authored by Ahmed Hosny

Since Specialization
Citations

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

Fields of papers citing papers by Ahmed Hosny

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ahmed Hosny

This figure shows the co-authorship network connecting the top 25 collaborators of Ahmed Hosny. A scholar is included among the top collaborators of Ahmed Hosny 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 Ahmed Hosny. Ahmed Hosny 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
1.
Hosny, Ahmed, et al.. (2025). Identifying gas bearing sand using simultaneous pre-stack seismic inversion method: case study of the Simian field, Offshore Nile Delta, Egypt. Journal of Petroleum Exploration and Production Technology. 15(4). 3 indexed citations
2.
Pai, Suraj, Dennis Bontempi, Mateo Sokač, et al.. (2024). Foundation model for cancer imaging biomarkers. Nature Machine Intelligence. 6(3). 354–367. 63 indexed citations breakdown →
3.
Hosny, Ahmed, et al.. (2023). Application of platelet -rich fibrin with β-tricalcium phosphate for reconstruction of bone in periapical defects. Al-Azhar Journal of Dental Science. 26(1). 67–74. 1 indexed citations
4.
Ye, Zezhong, Jack M. Qian, Ahmed Hosny, et al.. (2022). Deep Learning–based Detection of Intravenous Contrast Enhancement on CT Scans. Radiology Artificial Intelligence. 4(3). e210285–e210285. 10 indexed citations
5.
Hosny, Ahmed, et al.. (2022). Moho undulations and high Poisson’s ratio beneath volcanic areas, west of Saudi Arabia: indication of asymmetric lithospheric uplift. Journal of Seismology. 26(2). 301–318. 1 indexed citations
6.
Hassan, Tamer, et al.. (2022). Contribution of interleukin 27 serum level to pathogenesis and prognosis in children with immune thrombocytopenia. Medicine. 101(25). e29504–e29504. 5 indexed citations
7.
Kann, Benjamin H., Ahmed Hosny, & Hugo J.W.L. Aerts. (2021). Artificial intelligence for clinical oncology. Cancer Cell. 39(7). 916–927. 204 indexed citations
8.
Torres, Felipe Soares, Shazia Akbar, Srinivas Raman, et al.. (2021). End-to-End Non–Small-Cell Lung Cancer Prognostication Using Deep Learning Applied to Pretreatment Computed Tomography. JCO Clinical Cancer Informatics. 5(5). 1141–1150. 7 indexed citations
9.
Xu, Yiwen, Ahmed Hosny, Roman Zeleznik, et al.. (2019). Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging. Clinical Cancer Research. 25(11). 3266–3275. 402 indexed citations breakdown →
10.
Yang, Ting, Ahmed Hosny, Zhifei Deng, et al.. (2019). Bioinspired design of flexible armor based on chiton scales. Nature Communications. 10(1). 5413–5413. 80 indexed citations
11.
Bader, Christoph, Sunanda Sharma, Tzu‐Chieh Tang, et al.. (2019). Hybrid Living Materials: Digital Design and Fabrication of 3D Multimaterial Structures with Programmable Biohybrid Surfaces. Advanced Functional Materials. 30(7). 62 indexed citations
12.
Hosny, Ahmed, Chintan Parmar, John Quackenbush, Lawrence H. Schwartz, & Hugo J.W.L. Aerts. (2018). Artificial intelligence in radiology. Nature reviews. Cancer. 18(8). 500–510. 2301 indexed citations breakdown →
13.
Hosny, Ahmed, Steven J. Keating, Beth Ripley, et al.. (2018). From Improved Diagnostics to Presurgical Planning: High-Resolution Functionally Graded Multimaterial 3D Printing of Biomedical Tomographic Data Sets. 3D Printing and Additive Manufacturing. 5(2). 103–113. 33 indexed citations
14.
Parisi, Laura, et al.. (2018). Earthquake swarm in non-volcanic areas of western Saudi Arabia: comparison of observations and imaging. EGU General Assembly Conference Abstracts. 16036. 2 indexed citations
15.
Bader, Christoph, et al.. (2018). Making data matter: Voxel printing for the digital fabrication of data across scales and domains. Science Advances. 4(5). eaas8652–eaas8652. 87 indexed citations
16.
Hosny, Ahmed, Chintan Parmar, Thibaud Coroller, et al.. (2018). Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study. PLoS Medicine. 15(11). e1002711–e1002711. 398 indexed citations breakdown →
17.
Hosny, Ahmed, Tatiana Kelil, Moses Mathur, et al.. (2018). Pre-procedural fit-testing of TAVR valves using parametric modeling and 3D printing. Journal of cardiovascular computed tomography. 13(1). 21–30. 43 indexed citations
18.
Griethuysen, Joost J. M. van, Andriy Fedorov, Chintan Parmar, et al.. (2017). Computational Radiomics System to Decode the Radiographic Phenotype. Cancer Research. 77(21). e104–e107. 4200 indexed citations breakdown →
19.
Hosny, Ahmed, et al.. (2017). Unlocking vendor-specific tags: Three-dimensional printing of echocardiographic data sets. Journal of Thoracic and Cardiovascular Surgery. 155(1). 143–145.e1. 9 indexed citations
20.
Hosny, Ahmed, et al.. (2013). Shallow subsurface structures and geotechnical characteristics of Tal El-Amarna area, middle Egypt. NRIAG Journal of Astronomy and Geophysics. 2(2). 212–222. 3 indexed citations

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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