Ali Raza
Impact in
- Health Informatics top 5%
-
- Artificial Intelligence in Healthcare
Papers in
-
- Anomaly Detection Techniques and Applications 5
- Machine Learning in Healthcare 4
- Sentiment Analysis and Opinion Mining 4
- Co-authors
- Kashif Munir (15 shared papers)Mubarak Almutairi (10 shared papers)Furqan Rustam (10 shared papers)Imran Ashraf (9 shared papers)Hafeez Ur Rehman Siddiqui (7 shared papers)Laith Abualigah (14 shared papers)Nagwan Abdel Samee (9 shared papers)Heming Jia (3 shared papers)
- Journals
- IEEE Access (24 papers)PeerJ Computer Science (7 papers)PLoS ONE (5 papers)Applied Sciences (3 papers)Scientific Reports (3 papers)
- Partner nations
- PakistanSaudi ArabiaSouth Korea
In The Last Decade
Ali Raza
67 papers receiving 937 citations
Peers
Comparison fields: 5 of 115
- Health Informatics 31
- Health Information Management 99
- Signal Processing 117
- Artificial Intelligence 282
- Computer Vision and Pattern Recognition 164
Countries citing papers authored by Ali Raza
This map shows the geographic impact of Ali Raza'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 Ali Raza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ali Raza more than expected).
Fields of papers citing papers by Ali Raza
This network shows the impact of papers produced by Ali Raza. 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 Ali Raza. The network helps show where Ali Raza may publish in the future.
Co-authors
The 25 scholars most cited alongside Ali Raza, 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 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 107 | |
| 2 | 2022 | 83 | |
| 3 | 2022 | 56 | |
| 4 | 2022 | 49 | |
| 5 | 2023 | 42 | |
| 6 | 2023 | 37 | |
| 7 | 2023 | 33 | |
| 8 | 2023 | 32 | |
| 9 | 2023 | 31 | |
| 10 | 2023 | 27 | |
| 11 | 2024 | 24 | |
| 12 | 2024 | 22 | |
| 13 | 2022 | 21 | |
| 14 | 2023 | 20 | |
| 15 | 2023 | 20 | |
| 16 | 2023 | 18 | |
| 17 | 2023 | 18 | |
| 18 | 2023 | 18 | |
| 19 | 2023 | 18 | |
| 20 | 2024 | 14 |
About Ali Raza
Ali Raza is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Health Information Management and Signal Processing, having authored 73 papers that have together received 983 indexed citations. Recurring topics across this work include Smart Agriculture and AI (9 papers), Artificial Intelligence in Healthcare (9 papers), Network Security and Intrusion Detection (8 papers), Advanced Malware Detection Techniques (7 papers), Anomaly Detection Techniques and Applications (5 papers), Machine Learning in Healthcare (4 papers), Sentiment Analysis and Opinion Mining (4 papers) and Medical Imaging and Analysis (4 papers). The work is most often cited by research in Health Informatics (31 citations), Health Information Management (99 citations), Signal Processing (117 citations), Artificial Intelligence (282 citations) and Computer Vision and Pattern Recognition (164 citations). Ali Raza has collaborated with scholars based in Pakistan, Saudi Arabia and South Korea. Frequent co-authors include Kashif Munir, Mubarak Almutairi, Furqan Rustam, Imran Ashraf, Hafeez Ur Rehman Siddiqui, Laith Abualigah, Nagwan Abdel Samee, Heming Jia, Isabel de la Torre Díez and Maali Alabdulhafith. Their work appears in journals such as IEEE Access, PeerJ Computer Science, PLoS ONE, Applied Sciences and Scientific Reports.
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.