Danielle Power

30 total papers · 991 total citations
11 papers, 164 citations indexed

About

Danielle Power is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Danielle Power has authored 11 papers receiving a total of 164 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Pulmonary and Respiratory Medicine, 4 papers in Oncology and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Danielle Power's work include Lung Cancer Treatments and Mutations (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Cancer Genomics and Diagnostics (3 papers). Danielle Power is often cited by papers focused on Lung Cancer Treatments and Mutations (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Cancer Genomics and Diagnostics (3 papers). Danielle Power collaborates with scholars based in United Kingdom, Italy and Germany. Danielle Power's co-authors include Eric O. Aboagye, Haonan Lu, David J. Pinato, Mitchell Chen, Andrew Logan, Alessio Cortellini, Susan J. Copley, Patrizia Viola, Yidong Han and Henry Tam and has published in prestigious journals such as Journal of Clinical Oncology, Molecular Cancer Therapeutics and European Journal of Nuclear Medicine and Molecular Imaging.

In The Last Decade

Danielle Power

8 papers receiving 164 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Danielle Power	112	94	49	26	26	11	164
E.I. Eboulet	59 0.5×	123 1.3×	74 1.5×	14 0.5×	21 0.8×	15	167
Sandra Thierstein	96 0.9×	155 1.6×	42 0.9×	20 0.8×	29 1.1×	12	222
Iva Halilaj	210 1.9×	86 0.9×	49 1.0×	62 2.4×	65 2.5×	11	259
Athanasia Mitsala	78 0.7×	46 0.5×	102 2.1×	39 1.5×	19 0.7×	11	215
Aasheesh Kanwar	148 1.3×	53 0.6×	36 0.7×	30 1.2×	25 1.0×	7	190
Emmanuel Salinas-Miranda	98 0.9×	94 1.0×	56 1.1×	15 0.6×	20 0.8×	15	178
Xiaofeng Jiang	181 1.6×	55 0.6×	104 2.1×	62 2.4×	35 1.3×	13	268
Marika Reinius	76 0.7×	36 0.4×	46 0.9×	21 0.8×	34 1.3×	11	186
M Chetan	171 1.5×	121 1.3×	45 0.9×	13 0.5×	50 1.9×	13	227
Isabella Fornacon-Wood	213 1.9×	104 1.1×	42 0.9×	41 1.6×	74 2.8×	9	235

Countries citing papers authored by Danielle Power

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Danielle Power

This figure shows the co-authorship network connecting the top 25 collaborators of Danielle Power. A scholar is included among the top collaborators of Danielle Power based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Danielle Power. Danielle Power is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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