Farah E. Shamout

961 total citations
18 papers, 300 citations indexed

About

Farah E. Shamout is a scholar working on Artificial Intelligence, Epidemiology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Farah E. Shamout has authored 18 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Epidemiology and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Farah E. Shamout's work include Machine Learning in Healthcare (7 papers), Sepsis Diagnosis and Treatment (6 papers) and COVID-19 diagnosis using AI (4 papers). Farah E. Shamout is often cited by papers focused on Machine Learning in Healthcare (7 papers), Sepsis Diagnosis and Treatment (6 papers) and COVID-19 diagnosis using AI (4 papers). Farah E. Shamout collaborates with scholars based in United Kingdom, United Arab Emirates and United States. Farah E. Shamout's co-authors include David A. Clifton, Tingting Zhu, Peter Watkinson, Pulkit Sharma, James J. Choi, Rob Krams, Antonios N. Pouliopoulos, S. Farokh Atashzar, Vinayak Abrol and Lionel Tarassenko and has published in prestigious journals such as Scientific Reports, Communications of the ACM and BMJ Open.

In The Last Decade

Farah E. Shamout

15 papers receiving 289 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Farah E. Shamout United Kingdom 8 107 72 59 47 35 18 300
Boris Pfahringer Germany 4 122 1.1× 101 1.4× 24 0.4× 48 1.0× 35 1.0× 4 337
Jihye Lim South Korea 11 44 0.4× 81 1.1× 26 0.4× 49 1.0× 75 2.1× 31 374
Morgan Simons United States 6 155 1.4× 93 1.3× 34 0.6× 96 2.0× 31 0.9× 6 353
Anna Siefkas United States 9 81 0.8× 72 1.0× 27 0.5× 94 2.0× 36 1.0× 17 325
Aya Awad Israel 8 141 1.3× 100 1.4× 12 0.2× 29 0.6× 64 1.8× 10 343
Rahul Thapa United States 10 162 1.5× 45 0.6× 14 0.2× 52 1.1× 46 1.3× 15 354
Colleen M. Ennett Canada 10 122 1.1× 52 0.7× 29 0.5× 15 0.3× 59 1.7× 26 311
Martin Faltys Switzerland 5 117 1.1× 93 1.3× 21 0.4× 30 0.6× 25 0.7× 8 258
Thomas Gumbsch Switzerland 4 127 1.2× 89 1.2× 21 0.4× 31 0.7× 25 0.7× 8 270
Matthias Hüser Switzerland 4 121 1.1× 92 1.3× 21 0.4× 31 0.7× 25 0.7× 9 258

Countries citing papers authored by Farah E. Shamout

Since Specialization
Citations

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

Fields of papers citing papers by Farah E. Shamout

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Farah E. Shamout. 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 Farah E. Shamout. The network helps show where Farah E. Shamout may publish in the future.

Co-authorship network of co-authors of Farah E. Shamout

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

All Works

18 of 18 papers shown
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Shamout, Farah E., et al.. (2025). Meta-Repository of Screening Mammography Classifiers. Studies in health technology and informatics. 329. 1884–1885.
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Shamout, Farah E., et al.. (2024). Multimodal masked siamese network improves chest X-ray representation learning. Scientific Reports. 14(1). 22516–22516. 2 indexed citations
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Guerra-Manzanares, Alejandro, et al.. (2024). Multimodal Machine Learning for Stroke Prognosis and Diagnosis: A Systematic Review. IEEE Journal of Biomedical and Health Informatics. 28(11). 6958–6973. 11 indexed citations
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Shamout, Farah E., et al.. (2023). Deep learning for deterioration prediction of COVID-19 patients based on time-series of three vital signs. Scientific Reports. 13(1). 9968–9968. 7 indexed citations
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Johnson, David, et al.. (2022). An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates. Proceedings of the AAAI Conference on Artificial Intelligence. 36(11). 12766–12773. 6 indexed citations
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Sharma, Pulkit, Farah E. Shamout, Vinayak Abrol, & David A. Clifton. (2021). Data Pre-Processing Using Neural Processes for Modeling Personalized Vital-Sign Time-Series Data. IEEE Journal of Biomedical and Health Informatics. 26(4). 1528–1537. 11 indexed citations
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Almallah, Y. Zaki, Rania M. El-Lababidi, Farah E. Shamout, & D. John Doyle. (2021). Artificial Intelligence: The New Alexander Fleming. Healthcare Informatics Research. 27(2). 168–171. 4 indexed citations
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Youssef, Alexey, Samaneh Kouchaki, Farah E. Shamout, et al.. (2021). Development and validation of early warning score systems for COVID‐19 patients. Healthcare Technology Letters. 8(5). 105–117. 8 indexed citations
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Shamout, Farah E., et al.. (2021). The strategic pursuit of artificial intelligence in the United Arab Emirates. Communications of the ACM. 64(4). 57–58. 6 indexed citations
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Shamout, Farah E., Tingting Zhu, & David A. Clifton. (2020). Machine Learning for Clinical Outcome Prediction. IEEE Reviews in Biomedical Engineering. 14. 116–126. 124 indexed citations
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Wong, David, Stephen Gerry, Farah E. Shamout, et al.. (2020). Cross-sectional centiles of blood pressure by age and sex: a four-hospital database retrospective observational analysis. BMJ Open. 10(5). e033618–e033618. 2 indexed citations
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Shamout, Farah E., Tingting Zhu, Pulkit Sharma, Peter Watkinson, & David A. Clifton. (2019). Deep Interpretable Early Warning System for the Detection of Clinical Deterioration. IEEE Journal of Biomedical and Health Informatics. 24(2). 437–446. 61 indexed citations
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Shamout, Farah E., et al.. (2015). Enhancement of Non-Invasive Trans-Membrane Drug Delivery Using Ultrasound and Microbubbles During Physiologically Relevant Flow. Ultrasound in Medicine & Biology. 41(9). 2435–2448. 34 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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