Abdulqader M. Almars
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Sociology and Political Science
- Information Systems
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Ibrahim GadEl-Sayed AtlamTalal H. NoorMostafa A. ElhosseiniMahmoud BadawyEl‐Sayed AtlamMajed AlwateerHossam Magdy Balaha
- Topics
- Sentiment Analysis and Opinion Mining (4 papers)Misinformation and Its Impacts (3 papers)Network Security and Intrusion Detection (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessSensors
- Partner nations
- Saudi ArabiaEgyptUnited States
In The Last Decade
Abdulqader M. Almars
23 papers receiving 346 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 177
- Computer Vision and Pattern Recognition 95
- Sociology and Political Science 44
- Information Systems 41
- Radiology, Nuclear Medicine and Imaging 36
Countries citing papers authored by Abdulqader M. Almars
This map shows the geographic impact of Abdulqader M. Almars'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 Abdulqader M. Almars with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abdulqader M. Almars more than expected).
Fields of papers citing papers by Abdulqader M. Almars
This network shows the impact of papers produced by Abdulqader M. Almars. 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 Abdulqader M. Almars. The network helps show where Abdulqader M. Almars may publish in the future.
Co-authorship network of co-authors of Abdulqader M. Almars
This figure shows the co-authorship network connecting the top 25 collaborators of Abdulqader M. Almars. A scholar is included among the top collaborators of Abdulqader M. Almars 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 Abdulqader M. Almars. Abdulqader M. Almars is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 8 | |
| 8 | 13 | |
| 9 | 1 | |
| 10 | 27 | |
| 11 | 24 | |
| 12 | 27 | |
| 13 | 6 | |
| 14 | 0 | |
| 15 | 14 | |
| 16 | 15 | |
| 17 | 8 | |
| 18 | 4 | |
| 19 | 9 | |
| 20 | 73 |
About Abdulqader M. Almars
Abdulqader M. Almars is a scholar working on Health Information Management, Applied Psychology and Artificial Intelligence, having authored 27 papers that have together received 375 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (4 papers), Misinformation and Its Impacts (3 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Health Informatics (12 citations), Artificial Intelligence (177 citations) and Computer Vision and Pattern Recognition (95 citations). Abdulqader M. Almars has collaborated with scholars based in Saudi Arabia, Egypt and United States. Frequent co-authors include Ibrahim Gad, El-Sayed Atlam, Talal H. Noor, Mostafa A. Elhosseini, Mahmoud Badawy, El‐Sayed Atlam, Majed Alwateer, Hossam Magdy Balaha, Xin Zhao and Xue Li. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.
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.