David Laidley

771 citations
32 papers · 456 · h-index 11

Impact in

  • Neurology top 10%
    • Neuroblastoma Research and Treatments
    • Intracerebral and Subarachnoid Hemorrhage Research
    • Lung Cancer Research Studies

Papers in

David Laidley

28 papers receiving 445 citations

Peers

David Laidley
Comparison fields: 5 of 72
  • Neurology 153
  • Neurology 50
  • Oncology 143
  • Epidemiology 168
  • Radiology, Nuclear Medicine and Imaging 104
Replace Wojciech Ambrosius with:
Wojciech Ambrosius Poland
Long Di United States
Susanne Gellißen Germany
Yunyan Zhang Canada
Jianguo Xu China
Lara Harrison Finland
Yingmin Chen China
Yuyun Xu China
Benjamin Voellger Germany
J.-N. Vallée France
David Laidley relative to Wojciech Ambrosius Poland Wojciech Ambrosius's profile →
Citations per field
00.5×2.6×
Wojciech Ambrosius · 1×
Citations per year

Countries citing papers authored by David Laidley

Since Specialization
Citations

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

Fields of papers citing papers by David Laidley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Laidley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Laidley Line = papers co-authored together David Laidley links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201670
2 201663
3 202155
4 200545
5 201737
6 201834
7 201327
8 202121
9 200519
10 202019
11 198819
12 20236
13 20205
14 20225
15 20245
16 20235
17 20213
18 20213
19 20242
20 20202

About David Laidley

David Laidley is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Epidemiology, Neurology and Oncology, having authored 32 papers that have together received 456 indexed citations. Recurring topics across this work include Neuroendocrine Tumor Research Advances (10 papers), Radiopharmaceutical Chemistry and Applications (9 papers), Lung Cancer Research Studies (9 papers), Prostate Cancer Treatment and Research (9 papers), Medical Imaging Techniques and Applications (8 papers), Neuroblastoma Research and Treatments (7 papers), Prostate Cancer Diagnosis and Treatment (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Neurology (153 citations), Neurology (50 citations), Oncology (143 citations), Epidemiology (168 citations) and Radiology, Nuclear Medicine and Imaging (104 citations). David Laidley has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Shuo Li, Dale Corbett, Anat Kornecki, Mark Landis, Yunliang Cai, Andrea Lum, Aleksandra Szymanska, Jeff Biernaskie, Shirley Granter‐Button and Stephanie Leung. Their work appears in journals such as Journal of Clinical Oncology, International Journal of Radiation Oncology*Biology*Physics, Annals of Oncology, Experimental Neurology and Medical Physics.

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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