Amin Alqudah
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Co-authors
- Ali Mohammad AlqudahHiam AlquranIsam Abu‐QasmiehOlivier DebeirHussein Al-ZoubiV. ChandrasekarMinda LeMahmood Al-khassaweneh
- Topics
- AI in cancer detection (6 papers)Radiomics and Machine Learning in Medical Imaging (5 papers)Digital Imaging for Blood Diseases (4 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionEnergy Engineering and Power Technology
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEApplied Sciences
- Partner nations
- JordanUnited StatesSaudi Arabia
In The Last Decade
Amin Alqudah
31 papers receiving 390 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 138
- Radiology, Nuclear Medicine and Imaging 129
- Computer Vision and Pattern Recognition 112
- Computer Networks and Communications 45
- Electrical and Electronic Engineering 36
Countries citing papers authored by Amin Alqudah
This map shows the geographic impact of Amin Alqudah'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 Amin Alqudah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amin Alqudah more than expected).
Fields of papers citing papers by Amin Alqudah
This network shows the impact of papers produced by Amin Alqudah. 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 Amin Alqudah. The network helps show where Amin Alqudah may publish in the future.
Co-authorship network of co-authors of Amin Alqudah
This figure shows the co-authorship network connecting the top 25 collaborators of Amin Alqudah. A scholar is included among the top collaborators of Amin Alqudah 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 Amin Alqudah. Amin Alqudah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 1 | |
| 3 | 15 | |
| 4 | 33 | |
| 5 | 8 | |
| 6 | 14 | |
| 7 | 22 | |
| 8 | 20 | |
| 9 | 2 | |
| 10 | 8 | |
| 11 | 46 | |
| 12 | 2 | |
| 13 | 23 | |
| 14 | 22 | |
| 15 | 7 | |
| 16 | 2 | |
| 17 | 18 | |
| 18 | 15 | |
| 19 | 0 | |
| 20 | 1 |
About Amin Alqudah
Amin Alqudah is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Energy Engineering and Power Technology, having authored 32 papers that have together received 413 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Digital Imaging for Blood Diseases (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (129 citations), Computer Vision and Pattern Recognition (112 citations) and Energy Engineering and Power Technology (14 citations). Amin Alqudah has collaborated with scholars based in Jordan, United States and Saudi Arabia. Frequent co-authors include Ali Mohammad Alqudah, Hiam Alquran, Isam Abu‐Qasmieh, Olivier Debeir, Hussein Al-Zoubi, V. Chandrasekar, Minda Le, Mahmood Al-khassaweneh, Howard Jay Siegel and Jay Smith. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Applied Sciences.
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.