Ibrahem Kandel
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Plant Science
- Co-authors
- Mauro CastelliAleš PopovičLuca Manzoni
- Topics
- Digital Imaging for Blood Diseases (5 papers)AI in cancer detection (5 papers)COVID-19 diagnosis using AI (4 papers)
In The Last Decade
Ibrahem Kandel
9 papers receiving 686 citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Radiology, Nuclear Medicine and Imaging 216
- Artificial Intelligence 204
- Computer Vision and Pattern Recognition 201
- Biomedical Engineering 79
- Plant Science 48
Countries citing papers authored by Ibrahem Kandel
This map shows the geographic impact of Ibrahem Kandel'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 Ibrahem Kandel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ibrahem Kandel more than expected).
Fields of papers citing papers by Ibrahem Kandel
This network shows the impact of papers produced by Ibrahem Kandel. 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 Ibrahem Kandel. The network helps show where Ibrahem Kandel may publish in the future.
Co-authorship network of co-authors of Ibrahem Kandel
This figure shows the co-authorship network connecting the top 25 collaborators of Ibrahem Kandel. A scholar is included among the top collaborators of Ibrahem Kandel 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 Ibrahem Kandel. Ibrahem Kandel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 38 | |
| 2 | 17 | |
| 3 | 29 | |
| 4 | 115 | |
| 5 | 51 | |
| 6 | 58 | |
| 7 | 14 | |
| 8 | The effect of batch size on the generalizability of the convolutional neural networks on a histopathology datasetbreakdown → | 363 |
| 9 | 25 |
About Ibrahem Kandel
Ibrahem Kandel is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 710 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (5 papers), AI in cancer detection (5 papers) and COVID-19 diagnosis using AI (4 papers). The work is most often cited by research in Health Informatics (27 citations), Computer Vision and Pattern Recognition (201 citations) and Radiology, Nuclear Medicine and Imaging (216 citations). Ibrahem Kandel has collaborated with scholars based in Portugal, Slovenia and Italy. Frequent co-authors include Mauro Castelli, Aleš Popovič and Luca Manzoni. Their work appears in journals such as Applied Sciences, ICT Express and Emerging Science Journal.
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.