Ali Sadeghi‐Naini
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Biomedical Engineering top 5%
- Artificial Intelligence top 2%
- Pulmonary and Respiratory Medicine top 10%
- Cancer Research top 10%
- Co-authors
- Gregory J. CzarnotaWilliam T. TranHadi TadayyonLakshmanan SannachiSonal GandhiFrances C. WrightAbbas SamaniOmar Falou
- Topics
- Radiomics and Machine Learning in Medical Imaging (46 papers)Ultrasound Imaging and Elastography (35 papers)Photoacoustic and Ultrasonic Imaging (33 papers)
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Ali Sadeghi‐Naini
104 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 121
- Radiology, Nuclear Medicine and Imaging 1.6k
- Biomedical Engineering 750
- Artificial Intelligence 672
- Pulmonary and Respiratory Medicine 281
- Cancer Research 238
Countries citing papers authored by Ali Sadeghi‐Naini
This map shows the geographic impact of Ali Sadeghi‐Naini'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 Ali Sadeghi‐Naini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ali Sadeghi‐Naini more than expected).
Fields of papers citing papers by Ali Sadeghi‐Naini
This network shows the impact of papers produced by Ali Sadeghi‐Naini. 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 Ali Sadeghi‐Naini. The network helps show where Ali Sadeghi‐Naini may publish in the future.
Co-authorship network of co-authors of Ali Sadeghi‐Naini
This figure shows the co-authorship network connecting the top 25 collaborators of Ali Sadeghi‐Naini. A scholar is included among the top collaborators of Ali Sadeghi‐Naini 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 Ali Sadeghi‐Naini. Ali Sadeghi‐Naini 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 | 1 | |
| 3 | 10 | |
| 4 | 3 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 13 | |
| 8 | 10 | |
| 9 | 11 | |
| 10 | 15 | |
| 11 | 48 | |
| 12 | 48 | |
| 13 | 22 | |
| 14 | 19 | |
| 15 | 54 | |
| 16 | 48 | |
| 17 | 5 | |
| 18 | 42 | |
| 19 | 25 | |
| 20 | 56 |
About Ali Sadeghi‐Naini
Ali Sadeghi‐Naini is a scholar working on Radiology, Nuclear Medicine and Imaging, Biophysics and Radiation, having authored 109 papers that have together received 2.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (46 papers), Ultrasound Imaging and Elastography (35 papers) and Photoacoustic and Ultrasonic Imaging (33 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.6k citations), Health Informatics (61 citations) and Biophysics (137 citations). Ali Sadeghi‐Naini has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Gregory J. Czarnota, William T. Tran, Hadi Tadayyon, Lakshmanan Sannachi, Sonal Gandhi, Frances C. Wright, Abbas Samani, Omar Falou, Maureen Trudeau and Michael C. Kolios. Their work appears in journals such as PLoS ONE, Scientific Reports and Clinical Cancer Research.
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.