Ibrahim Abunadi
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Ebrahim Mohammed SenanAmjad RehmanTanzila SabaFahd N. Al‐WesabiMamdouh AleneziSuliman Mohamed FatiSouad Larabi-Marie-SainteManar Ahmed Hamza
- Topics
- AI in cancer detection (9 papers)COVID-19 diagnosis using AI (7 papers)IoT and Edge/Fog Computing (5 papers)
- Journals
- Scientific ReportsIEEE AccessSensors
- Partner nations
- Saudi ArabiaPakistanIndia
In The Last Decade
Ibrahim Abunadi
44 papers receiving 848 citations
Peers
Comparison fields: 5 of 120
- Artificial Intelligence 363
- Radiology, Nuclear Medicine and Imaging 213
- Information Systems 157
- Computer Vision and Pattern Recognition 156
- Computer Networks and Communications 115
Countries citing papers authored by Ibrahim Abunadi
This map shows the geographic impact of Ibrahim Abunadi'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 Ibrahim Abunadi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ibrahim Abunadi more than expected).
Fields of papers citing papers by Ibrahim Abunadi
This network shows the impact of papers produced by Ibrahim Abunadi. 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 Ibrahim Abunadi. The network helps show where Ibrahim Abunadi may publish in the future.
Co-authorship network of co-authors of Ibrahim Abunadi
This figure shows the co-authorship network connecting the top 25 collaborators of Ibrahim Abunadi. A scholar is included among the top collaborators of Ibrahim Abunadi 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 Ibrahim Abunadi. Ibrahim Abunadi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 17 | |
| 5 | 26 | |
| 6 | 24 | |
| 7 | 58 | |
| 8 | 49 | |
| 9 | 26 | |
| 10 | 7 | |
| 11 | 35 | |
| 12 | 8 | |
| 13 | 38 | |
| 14 | 49 | |
| 15 | 18 | |
| 16 | 17 | |
| 17 | 8 | |
| 18 | 1 | |
| 19 | 3 | |
| 20 | 14 |
About Ibrahim Abunadi
Ibrahim Abunadi is a scholar working on Health Informatics, Artificial Intelligence and Library and Information Sciences, having authored 46 papers that have together received 911 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), COVID-19 diagnosis using AI (7 papers) and IoT and Edge/Fog Computing (5 papers). The work is most often cited by research in Health Information Management (104 citations), Health Informatics (26 citations) and Artificial Intelligence (363 citations). Ibrahim Abunadi has collaborated with scholars based in Saudi Arabia, Pakistan and India. Frequent co-authors include Ebrahim Mohammed Senan, Amjad Rehman, Tanzila Saba, Fahd N. Al‐Wesabi, Mamdouh Alenezi, Suliman Mohamed Fati, Souad Larabi-Marie-Sainte, Manar Ahmed Hamza, Sanaa Ghouzali and Mukti E. Jadhav. Their work appears in journals such as Scientific Reports, 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.