Gail Darling

17.4k total citations · 3 hit papers
299 papers, 9.1k citations indexed

About

Gail Darling is a scholar working on Pulmonary and Respiratory Medicine, Surgery and Oncology. According to data from OpenAlex, Gail Darling has authored 299 papers receiving a total of 9.1k indexed citations (citations by other indexed papers that have themselves been cited), including 200 papers in Pulmonary and Respiratory Medicine, 144 papers in Surgery and 80 papers in Oncology. Recurrent topics in Gail Darling's work include Lung Cancer Diagnosis and Treatment (111 papers), Esophageal Cancer Research and Treatment (94 papers) and Lung Cancer Treatments and Mutations (67 papers). Gail Darling is often cited by papers focused on Lung Cancer Diagnosis and Treatment (111 papers), Esophageal Cancer Research and Treatment (94 papers) and Lung Cancer Treatments and Mutations (67 papers). Gail Darling collaborates with scholars based in Canada, United States and New Zealand. Gail Darling's co-authors include Shaf Keshavjee, Thomas K. Waddell, Frances A. Shepherd, Valerie W. Rusch, Andrew Pierre, Mark S. Allen, Richard Inculet, Marc de Perrot, Joe B. Putnam and David R. Jones and has published in prestigious journals such as The Lancet, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Gail Darling

284 papers receiving 8.9k citations

Hit Papers

Radiotherapy plus chemotherapy with or without surgical r... 2009 2026 2014 2020 2009 2011 2011 250 500 750

Peers

Gail Darling
Comparison fields: 5 of 140
  • Pulmonary and Respiratory Medicine 6.5k
  • Surgery 2.8k
  • Oncology 2.0k
  • Radiology, Nuclear Medicine and Imaging 1.2k
  • Molecular Biology 682
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Citations per field, relative to Gail Darling
Gail Darling · 1×
Citations per year, relative to Gail Darling
Gail Darling · 1×

Countries citing papers authored by Gail Darling

Since Specialization
Citations

This map shows the geographic impact of Gail Darling'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 Gail Darling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gail Darling more than expected).

Fields of papers citing papers by Gail Darling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gail Darling. 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 Gail Darling. The network helps show where Gail Darling may publish in the future.

Co-authorship network of co-authors of Gail Darling

This figure shows the co-authorship network connecting the top 25 collaborators of Gail Darling. A scholar is included among the top collaborators of Gail Darling 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 Gail Darling. Gail Darling is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 1
4 17
5 1
6 3
7 4
8 0
9 4
10 2
11 4
12 21
13 2
14 44
15 54
16 22
17 192
18 189
19
Lung cancer screening with low-dose computed tomography: Canadian experience.
40
20 72

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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