Khaled Al-Thelaya
Impact in
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- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
- Finance top 10%
- Financial Markets and Investment Strategies
Papers in
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- Digital Imaging for Blood Diseases 3
- Medical Image Segmentation Techniques 2
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- AI in cancer detection 5
- Co-authors
- El-Sayed M. El-Alfy (4 shared papers)Salahadin Mohammed (3 shared papers)Marco Agus (12 shared papers)Jens Schneider (11 shared papers)Mahmood Alzubaidi (5 shared papers)Mowafa Househ (3 shared papers)Alanoud Al‐Maadid (1 shared paper)Michel Makhlouf (2 shared papers)
- Journals
- Journal of Pathology Informatics (3 papers)IEEE Access (2 papers)iScience (1 paper)Computers & Graphics (1 paper)Multimedia Tools and Applications (1 paper)
- Partner nations
- QatarSaudi ArabiaItaly
In The Last Decade
Khaled Al-Thelaya
17 papers receiving 343 citations
Peers
Comparison fields: 5 of 85
- Management Science and Operations Research 166
- Finance 47
- Signal Processing 43
- Health Informatics 5
- Artificial Intelligence 81
Countries citing papers authored by Khaled Al-Thelaya
This map shows the geographic impact of Khaled Al-Thelaya'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 Khaled Al-Thelaya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khaled Al-Thelaya more than expected).
Fields of papers citing papers by Khaled Al-Thelaya
This network shows the impact of papers produced by Khaled Al-Thelaya. 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 Khaled Al-Thelaya. The network helps show where Khaled Al-Thelaya may publish in the future.
Co-authors
The 25 scholars most cited alongside Khaled Al-Thelaya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 154 | |
| 2 | 2018 | 61 | |
| 3 | 2021 | 34 | |
| 4 | 2023 | 29 | |
| 5 | 2022 | 20 | |
| 6 | 2022 | 13 | |
| 7 | 2023 | 11 | |
| 8 | 2019 | 9 | |
| 9 | 2021 | 9 | |
| 10 | 2020 | 4 | |
| 11 | 2022 | 4 | |
| 12 | 2025 | 3 | |
| 13 | 2021 | 2 | |
| 14 | 2025 | 2 | |
| 15 | 2023 | 2 | |
| 16 | 2024 | 1 | |
| 17 | 2020 | 1 | |
| 18 | 2024 | 0 | |
| 19 | 2026 | 0 | |
| 20 | 2025 | 0 |
About Khaled Al-Thelaya
Khaled Al-Thelaya is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Management Science and Operations Research, Signal Processing and Radiology, Nuclear Medicine and Imaging, having authored 20 papers that have together received 359 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (5 papers), AI in cancer detection (5 papers), Digital Imaging for Blood Diseases (3 papers), Cell Image Analysis Techniques (3 papers), Time Series Analysis and Forecasting (3 papers), Medical Image Segmentation Techniques (2 papers), Energy Load and Power Forecasting (2 papers) and Forecasting Techniques and Applications (2 papers). The work is most often cited by research in Management Science and Operations Research (166 citations), Finance (47 citations), Signal Processing (43 citations), Health Informatics (5 citations) and Artificial Intelligence (81 citations). Khaled Al-Thelaya has collaborated with scholars based in Qatar, Saudi Arabia and Italy. Frequent co-authors include El-Sayed M. El-Alfy, Salahadin Mohammed, Marco Agus, Jens Schneider, Mahmood Alzubaidi, Mowafa Househ, Alanoud Al‐Maadid, Michel Makhlouf, Alaa Abd‐Alrazaq and Uzair Shah. Their work appears in journals such as Journal of Pathology Informatics, IEEE Access, iScience, Computers & Graphics and Multimedia Tools and Applications.
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.