Janet E. Bailey
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- Radiology practices and education 14
- Radiation Dose and Imaging 11
- Radiomics and Machine Learning in Medical Imaging 5
- Medical Imaging Techniques and Applications 5
- Artificial Intelligence top 5%
- AI in cancer detection 12
- Cancer Research top 10%
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- Digital Radiography and Breast Imaging 11
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- Global Cancer Incidence and Screening 6
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- Innovations in Medical Education 5
- Co-authors
- Mark A. HelvieMarilyn A. RoubidouxKatherine A. KleinHeang‐Ping ChanCaroline E. BlaneChintana ParamagulLubomir M. HadjiiskiBerkman Sahiner
- Journals
- Academic Radiology (11 papers)Radiology (9 papers)Journal of the American College of Radiology (5 papers)
- Partner nations
- United StatesSlovakiaItaly
In The Last Decade
Janet E. Bailey
46 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 100
- Radiology, Nuclear Medicine and Imaging 528
- Artificial Intelligence 396
- Cancer Research 161
- Pulmonary and Respiratory Medicine 349
- Critical Care and Intensive Care Medicine 52
Countries citing papers authored by Janet E. Bailey
This map shows the geographic impact of Janet E. Bailey'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 Janet E. Bailey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janet E. Bailey more than expected).
Fields of papers citing papers by Janet E. Bailey
This network shows the impact of papers produced by Janet E. Bailey. 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 Janet E. Bailey. The network helps show where Janet E. Bailey may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Janet E. Bailey, 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 | 2025 | 0 | |
| 2 | 2019 | 12 | |
| 3 | 2018 | 1 | |
| 4 | 2018 | 5 | |
| 5 | 2018 | 0 | |
| 6 | 2015 | 5 | |
| 7 | 2014 | 9 | |
| 8 | 2014 | 32 | |
| 9 | 2014 | 15 | |
| 10 | 2012 | 68 | |
| 11 | 2011 | 13 | |
| 12 | 2010 | 47 | |
| 13 | 2006 | 94 | |
| 14 | 2005 | 16 | |
| 15 | 2004 | 85 | |
| 16 | 2004 | 48 | |
| 17 | 2004 | 1 | |
| 18 | 2004 | 67 | |
| 19 | 2004 | 64 | |
| 20 | 2001 | 10 |
About Janet E. Bailey
Janet E. Bailey is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Critical Care and Intensive Care Medicine, having authored 49 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiology practices and education (14 papers), AI in cancer detection (12 papers), Radiation Dose and Imaging (11 papers), Digital Radiography and Breast Imaging (11 papers), Global Cancer Incidence and Screening (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Imaging Techniques and Applications (5 papers) and Innovations in Medical Education (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (528 citations), Artificial Intelligence (396 citations) and Cancer Research (161 citations). Janet E. Bailey has collaborated with scholars based in United States, Slovakia and Italy. Frequent co-authors include Mark A. Helvie, Marilyn A. Roubidoux, Katherine A. Klein, Heang‐Ping Chan, Caroline E. Blane, Chintana Paramagul, Lubomir M. Hadjiiski, Berkman Sahiner, Alexis V. Nees and Linda A. Wray. Their work appears in journals such as Academic Radiology, Radiology, Journal of the American College of Radiology, Medical Physics and International Journal of Radiation Oncology*Biology*Physics.
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.