Karen Drukker
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education 9
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- Radiomics and Machine Learning in Medical Imaging 59
- MRI in cancer diagnosis 28
- Medical Imaging Techniques and Applications 15
- COVID-19 diagnosis using AI 9
- Artificial Intelligence top 0.5%
- AI in cancer detection 52
- Radiation top 5%
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- Breast Lesions and Carcinomas 14
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- Digital Radiography and Breast Imaging 9
Karen Drukker
101 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Health Informatics 204
- Radiology, Nuclear Medicine and Imaging 2.4k
- Artificial Intelligence 1.6k
- Radiation 202
- Computer Vision and Pattern Recognition 445
Countries citing papers authored by Karen Drukker
This map shows the geographic impact of Karen Drukker'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 Karen Drukker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karen Drukker more than expected).
Fields of papers citing papers by Karen Drukker
This network shows the impact of papers produced by Karen Drukker. 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 Karen Drukker. The network helps show where Karen Drukker may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Karen Drukker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 3 | |
| 8 | 2021 | 4 | |
| 9 | 2019 | 62 | |
| 10 | 2017 | 27 | |
| 11 | MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assaysbreakdown → | 2016 | 373 |
| 12 | Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data setbreakdown → | 2016 | 287 |
| 13 | 2014 | 25 | |
| 14 | 2014 | 11 | |
| 15 | 2013 | 24 | |
| 16 | 2008 | 43 | |
| 17 | 2005 | 43 | |
| 18 | 2005 | 28 | |
| 19 | 2002 | 178 | |
| 20 | 1996 | 54 |
About Karen Drukker
Karen Drukker is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 103 papers that have together received 3.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (59 papers), AI in cancer detection (52 papers), MRI in cancer diagnosis (28 papers), Medical Imaging Techniques and Applications (15 papers), Breast Lesions and Carcinomas (14 papers), COVID-19 diagnosis using AI (9 papers), Digital Radiography and Breast Imaging (9 papers) and Artificial Intelligence in Healthcare and Education (9 papers). The work is most often cited by research in Health Informatics (204 citations), Radiology, Nuclear Medicine and Imaging (2.4k citations) and Artificial Intelligence (1.6k citations). Karen Drukker has collaborated with scholars based in United States, Netherlands and China. Frequent co-authors include Maryellen L. Giger, George C. Schatz, Hui Li, Lubomir M. Hadjiiski, Berkman Sahiner, Yitan Zhu, H. Kenny, Yuan Ji, Aria Pezeshk and Ronald M. Summers. Their work appears in journals such as The Journal of Chemical Physics, The Journal of Physical Chemistry B and Cancer.
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.