Louise Wilkinson

2.1k total citations · 1 hit paper
42 papers, 1.2k citations indexed

About

Louise Wilkinson is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Louise Wilkinson has authored 42 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 24 papers in Pulmonary and Respiratory Medicine and 19 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Louise Wilkinson's work include AI in cancer detection (26 papers), Digital Radiography and Breast Imaging (23 papers) and Breast Lesions and Carcinomas (9 papers). Louise Wilkinson is often cited by papers focused on AI in cancer detection (26 papers), Digital Radiography and Breast Imaging (23 papers) and Breast Lesions and Carcinomas (9 papers). Louise Wilkinson collaborates with scholars based in United Kingdom, United States and France. Louise Wilkinson's co-authors include Toral Gathani, Nisha Sharma, Val Thomas, Rosalind Given-Wilson, Sue Hudson, R A Shinton, D G Beevers, Ivan J. Perry, Samantha L. Heller and Henry Potts and has published in prestigious journals such as British Journal of Cancer, Physics in Medicine and Biology and Medical Physics.

In The Last Decade

Louise Wilkinson

41 papers receiving 1.2k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Understanding breast cancer as a global health concern

2021 696 citations Louise Wilkinson et al. British Journal of Radiology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Louise Wilkinson United Kingdom	13	378	284	272	265	264	42	1.2k
Amritha Suresh India	24	349 0.9×	187 0.7×	173 0.6×	186 0.7×	262 1.0×	74	1.6k
Tai‐Kuang Chao Taiwan	23	194 0.5×	143 0.5×	248 0.9×	257 1.0×	270 1.0×	59	1.5k
Shaoyuan Lei China	9	443 1.2×	203 0.7×	125 0.5×	81 0.3×	196 0.7×	17	1.1k
Xiaorong Zhong China	20	475 1.3×	183 0.6×	158 0.6×	98 0.4×	452 1.7×	99	1.3k
Uma Krishnamurti United States	23	668 1.8×	194 0.7×	219 0.8×	65 0.2×	359 1.4×	55	1.4k
Andrzej Stanisławek Poland	7	412 1.1×	142 0.5×	101 0.4×	70 0.3×	260 1.0×	39	1.1k
Fiorella Guadagni Italy	18	237 0.6×	140 0.5×	137 0.5×	91 0.3×	149 0.6×	43	989
Toral Gathani United Kingdom	11	623 1.6×	141 0.5×	113 0.4×	88 0.3×	313 1.2×	26	1.3k
Mingfang Zhao China	22	347 0.9×	382 1.3×	183 0.7×	58 0.2×	179 0.7×	63	1.2k
Sergiusz Łukasiewicz Poland	2	382 1.0×	133 0.5×	101 0.4×	70 0.3×	247 0.9×	4	1.0k

Countries citing papers authored by Louise Wilkinson

Since Specialization

Citations

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

Fields of papers citing papers by Louise Wilkinson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Louise Wilkinson

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

All Works

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20 of 20 papers shown

Hudson, Sue, et al.. (2024). Percentage mammographic density or absolute breast density for risk stratification in breast screening: Possible implications for socioeconomic health disparity. Journal of Medical Screening. 32(2). 76–84.

Hudson, Sue, Louise Wilkinson, Bianca De Stavola, & Isabel dos‐Santos‐Silva. (2023). To what extent are objectively measured mammographic imaging techniques associated with compression outcomes. British Journal of Radiology. 96(1146). 20230089–20230089. 3 indexed citations

Wilkinson, Louise, et al.. (2023). Should we share breast density information during breast cancer screening in the United Kingdom? an integrative review. British Journal of Radiology. 96(1152). 20230122–20230122. 1 indexed citations

Young, Kenneth C., Mark Halling‐Brown, Stephen W. Duffy, et al.. (2023). Lessons learned from independent external validation of an AI tool to detect breast cancer using a representative UK data set. British Journal of Radiology. 96(1143). 20211104–20211104. 3 indexed citations

Chalkidou, Anastasia, Farhad Shokraneh, Sian Taylor‐Phillips, et al.. (2022). Recommendations for the development and use of imaging test sets to investigate the test performance of artificial intelligence in health screening. The Lancet Digital Health. 4(12). e899–e905. 14 indexed citations

Whelehan, Patricia, Sarah Vinnicombe, Graham Ball, et al.. (2021). Digital breast tomosynthesis: sensitivity for cancer in younger symptomatic women. British Journal of Radiology. 94(1119). 20201105–20201105. 6 indexed citations

Burnside, Elizabeth S., Lucy M. Warren, Jonathan P. Myles, et al.. (2021). Quantitative breast density analysis to predict interval and node-positive cancers in pursuit of improved screening protocols: a case–control study. British Journal of Cancer. 125(6). 884–892. 6 indexed citations

Duffy, Stephen W., J. A. Simpson, Matthew Wallis, et al.. (2020). Radiological audit of interval breast cancers: Estimation of tumour growth rates. The Breast. 51. 114–119. 12 indexed citations

Heller, Samantha L., et al.. (2018). Parenchymal pattern in women with dense breasts. Variation with age and impact on screening outcomes: observations from a UK screening programme. European Radiology. 28(11). 4717–4724. 2 indexed citations

10.

Elangovan, Premkumar, Alistair Mackenzie, David R. Dance, et al.. (2017). Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials. Physics in Medicine and Biology. 62(7). 2778–2794. 33 indexed citations

11.

Wilkinson, Louise, Val Thomas, & Nisha Sharma. (2016). Microcalcification on mammography: approaches to interpretation and biopsy. British Journal of Radiology. 90(1069). 20160594–20160594. 82 indexed citations

12.

Heller, Samantha L., Sue Hudson, & Louise Wilkinson. (2015). Breast density across a regional screening population: effects of age, ethnicity and deprivation. British Journal of Radiology. 88(1055). 20150242–20150242. 32 indexed citations

13.

Wilkinson, Louise, et al.. (2015). Quantitative study: should vacuum-assisted biopsy be the first biopsy approach in breast interventional techniques in stereotactic guided microcalcifications rather than 14 gauge core needle biopsy?. Breast Cancer Research. 17(S1). 1 indexed citations

14.

Gay, Hiram A., et al.. (2013). PB.13: Comparison between analogue and digital mammography: a reader's perspective. Breast Cancer Research. 15(S1). 1 indexed citations

15.

Pereira, Snehal M. Pinto, John H. Hipwell, Valerie McCormack, et al.. (2010). Automated registration of diagnostic to prediagnostic x‐ray mammograms: Evaluation and comparison to radiologists’ accuracy. Medical Physics. 37(9). 4530–4539. 7 indexed citations

16.

Taylor, Paul, et al.. (2008). Individualised training to address variability of radiologists' performance. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6917. 69170G–69170G. 7 indexed citations

17.

Taylor, Paul, et al.. (2007). An ontology for breast radiologist training. UCL Discovery (University College London). 190–195. 1 indexed citations

18.

Taylor, Paul, Rob Procter, Mark Hartswood, et al.. (2005). Distributed Intelligent Learning Environment for Screening Mammography. UCL Discovery (University College London). 2 indexed citations

19.

Wilkinson, Louise, et al.. (2005). Increasing the diagnosis of multifocal primary breast cancer by the use of bilateral whole-breast ultrasound. Clinical Radiology. 60(5). 573–578. 48 indexed citations

20.

Wilkinson, Louise, et al.. (1996). Biliary sludge: can ultrasound reliably detect the presence of crystals in bile?. European Journal of Gastroenterology & Hepatology. 8(10). 999–1001. 13 indexed citations

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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