Idit Diamant
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 1%
- Biomedical Engineering
- Pulmonary and Respiratory Medicine
- Co-authors
- Hayit GreenspanEyal KlangJacob GoldbergerMichal Marianne AmitaiMaayan Frid-AdarLior WolfYaniv BarEli Konen
- Topics
- AI in cancer detection (10 papers)Radiomics and Machine Learning in Medical Imaging (7 papers)Image Retrieval and Classification Techniques (6 papers)
- Cited by
- Health InformaticsComputer Vision and Pattern RecognitionRadiology, Nuclear Medicine and Imaging
- Partner nations
- IsraelUnited States
In The Last Decade
Idit Diamant
19 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Artificial Intelligence 868
- Radiology, Nuclear Medicine and Imaging 752
- Computer Vision and Pattern Recognition 686
- Biomedical Engineering 219
- Pulmonary and Respiratory Medicine 152
Countries citing papers authored by Idit Diamant
This map shows the geographic impact of Idit Diamant'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 Idit Diamant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Idit Diamant more than expected).
Fields of papers citing papers by Idit Diamant
This network shows the impact of papers produced by Idit Diamant. 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 Idit Diamant. The network helps show where Idit Diamant may publish in the future.
Co-authorship network of co-authors of Idit Diamant
This figure shows the co-authorship network connecting the top 25 collaborators of Idit Diamant. A scholar is included among the top collaborators of Idit Diamant 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 Idit Diamant. Idit Diamant is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classificationbreakdown → | 1210 |
| 2 | 29 | |
| 3 | 43 | |
| 4 | 26 | |
| 5 | 1 | |
| 6 | 198 | |
| 7 | 8 | |
| 8 | 13 | |
| 9 | 27 | |
| 10 | 244 | |
| 11 | 10 | |
| 12 | 6 | |
| 13 | 8 | |
| 14 | 4 | |
| 15 | 3 | |
| 16 | 6 | |
| 17 | 5 | |
| 18 | 25 | |
| 19 | 17 |
About Idit Diamant
Idit Diamant is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Orthopedics and Sports Medicine, having authored 19 papers that have together received 1.9k indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Image Retrieval and Classification Techniques (6 papers). The work is most often cited by research in Health Informatics (76 citations), Computer Vision and Pattern Recognition (686 citations) and Radiology, Nuclear Medicine and Imaging (752 citations). Idit Diamant has collaborated with scholars based in Israel and United States. Frequent co-authors include Hayit Greenspan, Eyal Klang, Jacob Goldberger, Michal Marianne Amitai, Maayan Frid-Adar, Lior Wolf, Yaniv Bar, Eli Konen, Sivan Lieberman and Amit Gefen. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Neurocomputing and Clinical Biomechanics.
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.