Danielle Power
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 Treatments and Mutations 6
- Lung Cancer Diagnosis and Treatment 3
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- Cancer Genomics and Diagnostics 3
- Co-authors
- Eric O. Aboagye (4 shared papers)Haonan Lu (2 shared papers)David J. Pinato (3 shared papers)Alessio Cortellini (1 shared paper)Andrew Logan (1 shared paper)Patrizia Viola (1 shared paper)Susan J. Copley (1 shared paper)Yidong Han (1 shared paper)
- Journals
- Journal of Clinical Oncology (2 papers)Lung Cancer (2 papers)Molecular Cancer Therapeutics (1 paper)Journal of Thoracic Oncology (1 paper)EBioMedicine (1 paper)
- Partner nations
- United KingdomItalySouth Korea
In The Last Decade
Danielle Power
8 papers receiving 168 citations
Peers
Comparison fields: 5 of 33
- Radiology, Nuclear Medicine and Imaging 115
- Health Informatics 6
- Pulmonary and Respiratory Medicine 97
- Oncology 50
- Hepatology 8
Countries citing papers authored by Danielle Power
This map shows the geographic impact of Danielle Power'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 Danielle Power with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Power more than expected).
Fields of papers citing papers by Danielle Power
This network shows the impact of papers produced by Danielle Power. 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 Danielle Power. The network helps show where Danielle Power may publish in the future.
Co-authors
The 25 scholars most cited alongside Danielle Power, 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 | 53 | |
| 2 | 2023 | 40 | |
| 3 | 2022 | 36 | |
| 4 | 2019 | 12 | |
| 5 | 2020 | 11 | |
| 6 | 2022 | 9 | |
| 7 | 1995 | 5 | |
| 8 | 2019 | 2 | |
| 9 | 2023 | 0 | |
| 10 | 2024 | 0 | |
| 11 | 2022 | 0 |
About Danielle Power
Danielle Power is a scholar working on Pulmonary and Respiratory Medicine, Cancer Research, Applied Psychology, Radiology, Nuclear Medicine and Imaging and Oncology, having authored 11 papers that have together received 168 indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Lung Cancer Diagnosis and Treatment (3 papers), Cancer Genomics and Diagnostics (3 papers), Colorectal Cancer Treatments and Studies (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (115 citations), Health Informatics (6 citations), Pulmonary and Respiratory Medicine (97 citations), Oncology (50 citations) and Hepatology (8 citations). Danielle Power has collaborated with scholars based in United Kingdom, Italy and South Korea. Frequent co-authors include Eric O. Aboagye, Haonan Lu, David J. Pinato, Alessio Cortellini, Andrew Logan, Patrizia Viola, Susan J. Copley, Yidong Han, Mitchell Chen and Andrea Rockall. Their work appears in journals such as Journal of Clinical Oncology, Lung Cancer, Molecular Cancer Therapeutics, Journal of Thoracic Oncology and EBioMedicine.
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.