Navid Farahani
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Biophysics top 2%
- Computer Vision and Pattern Recognition top 5%
- Molecular Biology
- Co-authors
- Liron PantanowitzAnil V. ParwaniDouglas J. HartmanDouglas BowmanAlbert XthonaMark D. ZarellaFamke AeffnerMarilyn M. Bui
- Topics
- AI in cancer detection (9 papers)Cell Image Analysis Techniques (5 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaNature ProtocolsAmerican Journal of Clinical Pathology
- Partner nations
- United StatesNetherlandsSweden
In The Last Decade
Navid Farahani
16 papers receiving 800 citations
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 461
- Radiology, Nuclear Medicine and Imaging 261
- Biophysics 173
- Computer Vision and Pattern Recognition 163
- Molecular Biology 115
Countries citing papers authored by Navid Farahani
This map shows the geographic impact of Navid Farahani'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 Navid Farahani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Navid Farahani more than expected).
Fields of papers citing papers by Navid Farahani
This network shows the impact of papers produced by Navid Farahani. 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 Navid Farahani. The network helps show where Navid Farahani may publish in the future.
Co-authorship network of co-authors of Navid Farahani
This figure shows the co-authorship network connecting the top 25 collaborators of Navid Farahani. A scholar is included among the top collaborators of Navid Farahani 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 Navid Farahani. Navid Farahani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 8 | |
| 3 | 13 | |
| 4 | 1 | |
| 5 | 38 | |
| 6 | 25 | |
| 7 | 10 | |
| 8 | 248 | |
| 9 | 5 | |
| 10 | 49 | |
| 11 | 23 | |
| 12 | 20 | |
| 13 | 52 | |
| 14 | 24 | |
| 15 | 51 | |
| 16 | 251 | |
| 17 | 0 |
About Navid Farahani
Navid Farahani is a scholar working on Biophysics, Artificial Intelligence and Health Information Management, having authored 17 papers that have together received 823 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Cell Image Analysis Techniques (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Biophysics (173 citations), Health Informatics (39 citations) and Artificial Intelligence (461 citations). Navid Farahani has collaborated with scholars based in United States, Netherlands and Sweden. Frequent co-authors include Liron Pantanowitz, Anil V. Parwani, Douglas J. Hartman, Douglas Bowman, Albert Xthona, Mark D. Zarella, Famke Aeffner, Marilyn M. Bui, Michael Riben and Yukako Yagi. Their work appears in journals such as SHILAP Revista de lepidopterología, Nature Protocols and American Journal of Clinical Pathology.
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.