Amir Moslemi
Impact in
-
- Face and Expression Recognition
- Image Retrieval and Classification Techniques
-
- Neural Networks and Applications
Papers in
-
- Machine Learning and ELM 3
- AI in cancer detection 3
-
- Chronic Obstructive Pulmonary Disease (COPD) Research 6
- Lung Cancer Diagnosis and Treatment 3
- Co-authors
- Miranda Kirby (8 shared papers)Wan C. Tan (4 shared papers)Jean Bourbeau (5 shared papers)James C. Hogg (4 shared papers)Susan A. Wood (1 shared paper)Konstantina Kontogianni (2 shared papers)Felix Herth (2 shared papers)Jason H. Li (1 shared paper)
- Journals
- Academic Radiology (3 papers)Computers in Biology and Medicine (3 papers)Medical Physics (2 papers)Engineering Applications of Artificial Intelligence (2 papers)Tomography (1 paper)
- Partner nations
- CanadaGermanyUnited States
In The Last Decade
Amir Moslemi
20 papers receiving 220 citations
Peers
Comparison fields: 5 of 63
- Computer Vision and Pattern Recognition 68
- Artificial Intelligence 78
- Health Informatics 3
- Health Information Management 7
- Radiology, Nuclear Medicine and Imaging 32
Countries citing papers authored by Amir Moslemi
This map shows the geographic impact of Amir Moslemi'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 Amir Moslemi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amir Moslemi more than expected).
Fields of papers citing papers by Amir Moslemi
This network shows the impact of papers produced by Amir Moslemi. 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 Amir Moslemi. The network helps show where Amir Moslemi may publish in the future.
Co-authors
The 25 scholars most cited alongside Amir Moslemi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 43 | |
| 2 | 2022 | 30 | |
| 3 | 2022 | 27 | |
| 4 | 2024 | 21 | |
| 5 | 2022 | 17 | |
| 6 | 2024 | 16 | |
| 7 | 2023 | 12 | |
| 8 | 2024 | 10 | |
| 9 | 2023 | 10 | |
| 10 | 2024 | 8 | |
| 11 | 2023 | 7 | |
| 12 | 2024 | 6 | |
| 13 | 2024 | 4 | |
| 14 | 2024 | 3 | |
| 15 | 2023 | 3 | |
| 16 | 2025 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2022 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2021 | 1 |
About Amir Moslemi
Amir Moslemi is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Molecular Biology, having authored 27 papers that have together received 222 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), Face and Expression Recognition (7 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (6 papers), Gene expression and cancer classification (3 papers), Lung Cancer Diagnosis and Treatment (3 papers), Machine Learning and ELM (3 papers), AI in cancer detection (3 papers) and Head and Neck Cancer Studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (68 citations), Artificial Intelligence (78 citations), Health Informatics (3 citations), Health Information Management (7 citations) and Radiology, Nuclear Medicine and Imaging (32 citations). Amir Moslemi has collaborated with scholars based in Canada, Germany and United States. Frequent co-authors include Miranda Kirby, Wan C. Tan, Jean Bourbeau, James C. Hogg, Susan A. Wood, Konstantina Kontogianni, Felix Herth, Jason H. Li, Harvey O. Coxson and Cameron Hague. Their work appears in journals such as Academic Radiology, Computers in Biology and Medicine, Medical Physics, Engineering Applications of Artificial Intelligence and Tomography.
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.