Mohammed Y. Kamil
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Neurology
- Pulmonary and Respiratory Medicine
- Topics
- AI in cancer detection (21 papers)Radiomics and Machine Learning in Medical Imaging (8 papers)Medical Image Segmentation Techniques (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Physics Conference SeriesInternational journal of intelligent engineering and systems
In The Last Decade
Mohammed Y. Kamil
31 papers receiving 295 citations
Peers
Comparison fields: 5 of 56
- Artificial Intelligence 192
- Radiology, Nuclear Medicine and Imaging 152
- Computer Vision and Pattern Recognition 78
- Neurology 51
- Pulmonary and Respiratory Medicine 33
Countries citing papers authored by Mohammed Y. Kamil
This map shows the geographic impact of Mohammed Y. Kamil'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 Mohammed Y. Kamil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed Y. Kamil more than expected).
Fields of papers citing papers by Mohammed Y. Kamil
This network shows the impact of papers produced by Mohammed Y. Kamil. 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 Mohammed Y. Kamil. The network helps show where Mohammed Y. Kamil may publish in the future.
Co-authorship network of co-authors of Mohammed Y. Kamil
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed Y. Kamil. A scholar is included among the top collaborators of Mohammed Y. Kamil 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 Mohammed Y. Kamil. Mohammed Y. Kamil 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 6 | |
| 13 | 10 | |
| 14 | 14 | |
| 15 | 6 | |
| 16 | 6 | |
| 17 | 9 | |
| 18 | 2 | |
| 19 | 38 | |
| 20 | Edge detection for Diabetic Retinopathy using fuzzy logic | 1 |
About Mohammed Y. Kamil
Mohammed Y. Kamil is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 39 papers that have together received 305 indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Medical Image Segmentation Techniques (6 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (152 citations), Neurology (51 citations) and Artificial Intelligence (192 citations). Mohammed Y. Kamil has collaborated with scholars based in Iraq, India and Nepal. Frequent co-authors include Abdullah Saleh, K. Balasubramani, K. Ravindran, Saravanan Thiyagarajan and Mazin Abed Mohammed. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Physics Conference Series and International journal of intelligent engineering and systems.
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.