Sue Hudson

1.0k total citations
40 papers, 362 citations indexed

About

Sue Hudson is a scholar working on Education, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Sue Hudson has authored 40 papers receiving a total of 362 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Education, 13 papers in Oncology and 10 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Sue Hudson's work include Global Cancer Incidence and Screening (13 papers), AI in cancer detection (10 papers) and Digital Radiography and Breast Imaging (10 papers). Sue Hudson is often cited by papers focused on Global Cancer Incidence and Screening (13 papers), AI in cancer detection (10 papers) and Digital Radiography and Breast Imaging (10 papers). Sue Hudson collaborates with scholars based in United Kingdom, Australia and Portugal. Sue Hudson's co-authors include Peter Hudson, Louise Wilkinson, Samantha L. Heller, Stephen W. Duffy, Isabel dos‐Santos‐Silva, Bianca De Stavola, Denise Beutel, Julietta Patnick, Judith Offman and Sarah Vinnicombe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, JAMA and Radiology.

In The Last Decade

Sue Hudson

36 papers receiving 321 citations

Peers

Sue Hudson

EDUCA

ONCOL

PRM

RNMI

Dianne Johnson United States

Melissa P. Johnston United States

Mathew S. Lopes United States

Renato Santos de Oliveira Filho Brazil

Moawia Mohammed Ali Elhassan Sudan

Jean S. Lee United States

Susie Chen United States

Pippa McKelvie‐Sebileau New Zealand

Linda Rainey Netherlands

Sahar Abbasi Iran

Dianne Johnson United States

Sue Hudson

20 ×0.2

EDUCA

117 ×1.0

ONCOL

67 ×0.8

PRM

43 ×0.6

48 ×0.9

RNMI

Citations per year, relative to Sue Hudson Sue Hudson (= 1×) peers Dianne Johnson

Countries citing papers authored by Sue Hudson

Since Specialization

Citations

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

Fields of papers citing papers by Sue Hudson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sue Hudson

This figure shows the co-authorship network connecting the top 25 collaborators of Sue Hudson. A scholar is included among the top collaborators of Sue Hudson 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 Sue Hudson. Sue Hudson 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

Hickman, Sarah, Nicholas Roy Payne, Yuan Huang, et al.. (2024). Deep Learning Algorithms for Breast Cancer Detection in a UK Screening Cohort: As Stand-alone Readers and Combined with Human Readers. Radiology. 313(2). e233147–e233147. 2 indexed citations

Taylor‐Phillips, Sian, Chris Stinton, Melina A. Kunar, et al.. (2024). Fatigue and vigilance in medical experts detecting breast cancer. Proceedings of the National Academy of Sciences. 121(11). e2309576121–e2309576121. 4 indexed citations

Haas, Elisabeth A. & Sue Hudson. (2024). Mentoring for Effective Teaching - An Analysis of Austrian Mentees’ School-based Mentoring Practices. Journal of Education and Training Studies. 13(1). 49–49.

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.

Payne, Nicholas Roy, Sarah Hickman, Richard Black, et al.. (2024). Breast density effect on the sensitivity of digital screening mammography in a UK cohort. European Radiology. 35(1). 177–187. 9 indexed citations

Hickman, Sarah, Nicholas Roy Payne, Yuan Huang, et al.. (2023). Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study. Radiology. 309(2). 13 indexed citations

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

Cooper, Jennifer, et al.. (2021). Optimising breast cancer screening reading: blinding the second reader to the first reader’s decisions. European Radiology. 32(1). 602–612. 2 indexed citations

Hudson, Sue. (2019). Lessons From the Heart: A Kinesthetic Activity for Practical Nursing Students. Nursing Education Perspectives. 41(3). 195–196. 1 indexed citations

10.

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

11.

Hudson, Sue, Kirsti Vik Hjerkind, Sarah Vinnicombe, et al.. (2018). Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk. Breast Cancer Research. 20(1). 156–156. 27 indexed citations

12.

Allgood, P C, Anthony Maxwell, Sue Hudson, et al.. (2016). A randomised trial of the effect of postal reminders on attendance for breast screening. British Journal of Cancer. 114(2). 171–176. 17 indexed citations

13.

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

14.

Hudson, Peter & Sue Hudson. (2014). Mentors’ and mentees’ views about desirable attributes and practices for preservice teachers. Acta Biologica Hungarica. 39(2-3). 229–49. 2 indexed citations

15.

Watters, James J., Sue Hudson, & Peter Hudson. (2013). Orienting preservice teachers towards gifted education : School university partnerships. QUT ePrints (Queensland University of Technology). 22(2). 32–44. 4 indexed citations

16.

Offman, Judith, Mary Wilson, Sue Hudson, et al.. (2013). A randomised trial of weekend and evening breast screening appointments. British Journal of Cancer. 109(3). 597–602. 18 indexed citations

17.

Hudson, Peter, et al.. (2012). Preservice teachers’ views : Issues for learning to teach SOSE in an overcrowded curriculum. Faculty of Education. 1 indexed citations

18.

Hudson, Sue. (2009). Preservice teachers’ perceptions of their middleschooling teacher preparation. ePublications@SCU (Southern Cross University). 1 indexed citations

19.

Hudson, Peter & Sue Hudson. (2007). Examining preservice teachers' preparedness for teaching art. International journal of education and the arts. 8(5). 1–25. 30 indexed citations

20.

Hudson, Sue & Peter Hudson. (2006). Beginning teachers’ perceptions of their tertiary education preparedness for teaching. QUT ePrints (Queensland University of Technology). 9(1). 1 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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