Berkman Sahiner
- Radiology, Nuclear Medicine and Imaging top 0.1%
- Artificial Intelligence top 0.1%
- Pulmonary and Respiratory Medicine top 0.5%
- Computer Vision and Pattern Recognition top 0.5%
- Oncology top 5%
- Co-authors
- Heang‐Ping ChanNicholas PetrickLubomir M. HadjiiskiMark A. HelvieMitchell M. GoodsittChuan ZhouDorit D. AdlerJun Wei
- Topics
- AI in cancer detection (157 papers)Radiomics and Machine Learning in Medical Imaging (139 papers)Digital Radiography and Breast Imaging (56 papers)
- Partner nations
- United StatesThailandMalaysia
In The Last Decade
Berkman Sahiner
284 papers receiving 7.7k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Radiology, Nuclear Medicine and Imaging 5.0k
- Artificial Intelligence 4.8k
- Pulmonary and Respiratory Medicine 2.6k
- Computer Vision and Pattern Recognition 2.1k
- Oncology 969
Countries citing papers authored by Berkman Sahiner
This map shows the geographic impact of Berkman Sahiner'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 Berkman Sahiner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Berkman Sahiner more than expected).
Fields of papers citing papers by Berkman Sahiner
This network shows the impact of papers produced by Berkman Sahiner. 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 Berkman Sahiner. The network helps show where Berkman Sahiner may publish in the future.
Co-authorship network of co-authors of Berkman Sahiner
This figure shows the co-authorship network connecting the top 25 collaborators of Berkman Sahiner. A scholar is included among the top collaborators of Berkman Sahiner 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 Berkman Sahiner. Berkman Sahiner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 77 | |
| 6 | 16 | |
| 7 | 19 | |
| 8 | 12 | |
| 9 | 114 | |
| 10 | Characterization of Mammographic Masses Based on Level Set Segmentation with New Image Features and Patient Information | 1 |
| 11 | 64 | |
| 12 | Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment | 2 |
| 13 | 31 | |
| 14 | Automatic multiscale enhancement and segmentation of pulmonary vessels in CT pulmonary angiography images for CAD applications | 2 |
| 15 | Application of boundary detection information in breast tomosynthesis reconstruction | 1 |
| 16 | 78 | |
| 17 | 211 | |
| 18 | 16 | |
| 19 | 105 | |
| 20 | 120 |
About Berkman Sahiner
Berkman Sahiner is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 294 papers that have together received 8.0k indexed citations. Recurring topics across this work include AI in cancer detection (157 papers), Radiomics and Machine Learning in Medical Imaging (139 papers) and Digital Radiography and Breast Imaging (56 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (5.0k citations), Health Informatics (286 citations) and Artificial Intelligence (4.8k citations). Berkman Sahiner has collaborated with scholars based in United States, Thailand and Malaysia. Frequent co-authors include Heang‐Ping Chan, Nicholas Petrick, Lubomir M. Hadjiiski, Mark A. Helvie, Mitchell M. Goodsitt, Chuan Zhou, Dorit D. Adler, Jun Wei, Aria Pezeshk and Ella A. Kazerooni. Their work appears in journals such as PLoS ONE, JNCI Journal of the National Cancer Institute and Radiology.
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.