Amy Lu
Impact in
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- Digital Radiography and Breast Imaging
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- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Digital Radiography and Breast Imaging 11
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- AI in cancer detection 7
- Co-authors
- David Gur (10 shared papers)Marie A. Ganott (10 shared papers)Jules H. Sumkin (9 shared papers)Andriy I. Bandos (8 shared papers)Margarita L. Zuley (10 shared papers)Luisa P. Wallace (5 shared papers)Amy E. Kelly (6 shared papers)Denise M. Chough (6 shared papers)
- Journals
- Radiology (4 papers)Academic Radiology (3 papers)Medical Physics (2 papers)Journal of Digital Imaging (2 papers)The American Journal of Gastroenterology (1 paper)
- Partner nations
- United States
In The Last Decade
Amy Lu
21 papers receiving 710 citations
Peers
Comparison fields: 5 of 59
- Pulmonary and Respiratory Medicine 405
- Radiology, Nuclear Medicine and Imaging 243
- Artificial Intelligence 334
- Cancer Research 65
- Computer Vision and Pattern Recognition 91
Countries citing papers authored by Amy Lu
This map shows the geographic impact of Amy Lu'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 Amy Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amy Lu more than expected).
Fields of papers citing papers by Amy Lu
This network shows the impact of papers produced by Amy Lu. 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 Amy Lu. The network helps show where Amy Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Amy Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 144 | |
| 2 | 2012 | 128 | |
| 3 | 2011 | 126 | |
| 4 | 2005 | 91 | |
| 5 | 2006 | 59 | |
| 6 | 2014 | 44 | |
| 7 | 2007 | 36 | |
| 8 | 2011 | 28 | |
| 9 | 2024 | 12 | |
| 10 | 2007 | 11 | |
| 11 | 2010 | 9 | |
| 12 | 2013 | 8 | |
| 13 | 2007 | 8 | |
| 14 | 2020 | 7 | |
| 15 | 2008 | 5 | |
| 16 | 2024 | 2 | |
| 17 | 2016 | 2 | |
| 18 | 2022 | 2 | |
| 19 | 2025 | 1 | |
| 20 | 2007 | 1 |
About Amy Lu
Amy Lu is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine and Cancer Research, having authored 21 papers that have together received 725 indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (11 papers), AI in cancer detection (7 papers), Breast Lesions and Carcinomas (4 papers), Radiology practices and education (3 papers), Breast Cancer Treatment Studies (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), MRI in cancer diagnosis (2 papers) and Radiation Dose and Imaging (2 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (405 citations), Radiology, Nuclear Medicine and Imaging (243 citations), Artificial Intelligence (334 citations), Cancer Research (65 citations) and Computer Vision and Pattern Recognition (91 citations). Amy Lu has collaborated with scholars based in United States. Frequent co-authors include David Gur, Marie A. Ganott, Jules H. Sumkin, Andriy I. Bandos, Margarita L. Zuley, Luisa P. Wallace, Amy E. Kelly, Denise M. Chough, Christiane M. Hakim and Victor J. Catullo. Their work appears in journals such as Radiology, Academic Radiology, Medical Physics, Journal of Digital Imaging and The American Journal of Gastroenterology.
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.