Kelsey Ayers
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
Papers in
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- Lung Cancer Diagnosis and Treatment 3
- Pleural and Pulmonary Diseases 1
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- Metabolism, Diabetes, and Cancer 1
- Co-authors
- Joseph B. Shrager (5 shared papers)Andrew Quon (2 shared papers)Weiruo Zhang (2 shared papers)Shaimaa Bakr (2 shared papers)Sandy Napel (2 shared papers)Sylvia K. Plevritis (2 shared papers)Mājid Shafiq (2 shared papers)Jalen Benson (3 shared papers)
- Journals
- Journal of Thoracic and Cardiovascular Surgery (1 paper)Scientific Reports (1 paper)Scientific Data (1 paper)Cancer Research (1 paper)Seminars in Thoracic and Cardiovascular Surgery (1 paper)
- Partner nations
- United StatesSouth KoreaChina
In The Last Decade
Kelsey Ayers
5 papers receiving 335 citations
Peers
Comparison fields: 5 of 67
- Radiology, Nuclear Medicine and Imaging 192
- Health Informatics 9
- Pulmonary and Respiratory Medicine 161
- Cancer Research 60
- Artificial Intelligence 81
Countries citing papers authored by Kelsey Ayers
This map shows the geographic impact of Kelsey Ayers'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 Kelsey Ayers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kelsey Ayers more than expected).
Fields of papers citing papers by Kelsey Ayers
This network shows the impact of papers produced by Kelsey Ayers. 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 Kelsey Ayers. The network helps show where Kelsey Ayers may publish in the future.
Co-authors
The 25 scholars most cited alongside Kelsey Ayers, 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 | 2018 | 209 | |
| 2 | 2018 | 87 | |
| 3 | 2017 | 24 | |
| 4 | 2021 | 12 | |
| 5 | 2017 | 6 |
About Kelsey Ayers
Kelsey Ayers is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Critical Care and Intensive Care Medicine, General Health Professions and Artificial Intelligence, having authored 5 papers that have together received 338 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (3 papers), AI in cancer detection (1 paper), Metabolism, Diabetes, and Cancer (1 paper), Palliative Care and End-of-Life Issues (1 paper), Cancer, Hypoxia, and Metabolism (1 paper), Patient-Provider Communication in Healthcare (1 paper), Pleural and Pulmonary Diseases (1 paper) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (192 citations), Health Informatics (9 citations), Pulmonary and Respiratory Medicine (161 citations), Cancer Research (60 citations) and Artificial Intelligence (81 citations). Kelsey Ayers has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Joseph B. Shrager, Andrew Quon, Weiruo Zhang, Shaimaa Bakr, Sandy Napel, Sylvia K. Plevritis, Mājid Shafiq, Jalen Benson, Mu Zhou and Hong Zheng. Their work appears in journals such as Journal of Thoracic and Cardiovascular Surgery, Scientific Reports, Scientific Data, Cancer Research and Seminars in Thoracic and Cardiovascular Surgery.
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.