M.A. Chyad
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Digital Imaging for Blood Diseases 1
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- Sentiment Analysis and Opinion Mining 1
- Co-authors
- A. A. Zaidan (9 shared papers)B. B. Zaidan (8 shared papers)A. H. Alamoodi (7 shared papers)O. S. Albahri (7 shared papers)A. S. Albahri (7 shared papers)K. I. Mohammed (3 shared papers)E. M. Almahdi (3 shared papers)Karrar Hameed Abdulkareem (4 shared papers)
In The Last Decade
M.A. Chyad
11 papers receiving 823 citations
M.A. Chyad's Hit Papers
Peers
Comparison fields: 5 of 113
- Health Informatics 53
- Health Information Management 49
- Artificial Intelligence 317
- Radiology, Nuclear Medicine and Imaging 180
- Modeling and Simulation 38
Countries citing papers authored by M.A. Chyad
This map shows the geographic impact of M.A. Chyad'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 M.A. Chyad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.A. Chyad more than expected).
Fields of papers citing papers by M.A. Chyad
This network shows the impact of papers produced by M.A. Chyad. 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 M.A. Chyad. The network helps show where M.A. Chyad may publish in the future.
Co-authors
The 25 scholars most cited alongside M.A. Chyad, 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 | Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review Hit paper breakdown → | 2020 | 269 |
| 2 | 2020 | 195 | |
| 3 | 2019 | 98 | |
| 4 | 2020 | 82 | |
| 5 | 2019 | 79 | |
| 6 | 2024 | 43 | |
| 7 | 2021 | 41 | |
| 8 | 2019 | 18 | |
| 9 | 2019 | 11 | |
| 10 | 2024 | 6 | |
| 11 | 2025 | 3 | |
| 12 | 2024 | 0 |
About M.A. Chyad
M.A. Chyad is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Radiology, Nuclear Medicine and Imaging and Human-Computer Interaction, having authored 12 papers that have together received 845 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (2 papers), Virtual Reality Applications and Impacts (2 papers), COVID-19 diagnosis using AI (2 papers), Artificial Intelligence in Healthcare (1 paper), Sentiment Analysis and Opinion Mining (1 paper), Digital Imaging for Blood Diseases (1 paper), Impact of AI and Big Data on Business and Society (1 paper) and Misinformation and Its Impacts (1 paper). The work is most often cited by research in Health Informatics (53 citations), Health Information Management (49 citations), Artificial Intelligence (317 citations), Radiology, Nuclear Medicine and Imaging (180 citations) and Modeling and Simulation (38 citations). M.A. Chyad has collaborated with scholars based in Malaysia, Iraq and Jordan. Frequent co-authors include A. A. Zaidan, B. B. Zaidan, A. H. Alamoodi, O. S. Albahri, A. S. Albahri, K. I. Mohammed, E. M. Almahdi, Karrar Hameed Abdulkareem, A.M. Aleesa and R. Q. Malik. Their work appears in journals such as IEEE Access, Computer Methods and Programs in Biomedicine, Journal of Infection and Public Health, Chaos Solitons & Fractals and Information Fusion.
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.