Andrew Beavis

1.4k total citations
71 papers, 948 citations indexed

About

Andrew Beavis is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Radiation. According to data from OpenAlex, Andrew Beavis has authored 71 papers receiving a total of 948 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Radiology, Nuclear Medicine and Imaging, 41 papers in Pulmonary and Respiratory Medicine and 39 papers in Radiation. Recurrent topics in Andrew Beavis's work include Advanced Radiotherapy Techniques (39 papers), Medical Imaging Techniques and Applications (21 papers) and Digital Radiography and Breast Imaging (18 papers). Andrew Beavis is often cited by papers focused on Advanced Radiotherapy Techniques (39 papers), Medical Imaging Techniques and Applications (21 papers) and Digital Radiography and Breast Imaging (18 papers). Andrew Beavis collaborates with scholars based in United Kingdom, United States and Canada. Andrew Beavis's co-authors include C S Moore, Gary Liney, James W. Ward, Pete Bridge, R. Appleyard, Peter Gibbs, S. Weston, John Greenman, R. J. Phillips and Michael Lind and has published in prestigious journals such as Scientific Reports, International Journal of Radiation Oncology*Biology*Physics and Computers & Education.

In The Last Decade

Andrew Beavis

67 papers receiving 927 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew Beavis United Kingdom 18 556 466 380 310 98 71 948
Richard Canters Netherlands 20 867 1.6× 493 1.1× 300 0.8× 1.1k 3.5× 85 0.9× 47 1.6k
Michel Féron Belgium 11 440 0.8× 357 0.8× 327 0.9× 164 0.5× 122 1.2× 41 945
Mika Kapanen Finland 21 951 1.7× 1.1k 2.3× 604 1.6× 327 1.1× 88 0.9× 70 1.5k
A. Tai United States 21 722 1.3× 773 1.7× 502 1.3× 144 0.5× 111 1.1× 77 1.4k
A Boyer United States 15 556 1.0× 698 1.5× 508 1.3× 134 0.4× 45 0.5× 40 945
Matthew B. Podgorsak United States 20 550 1.0× 828 1.8× 663 1.7× 174 0.6× 106 1.1× 81 1.1k
Devon Godfrey United States 17 1.0k 1.9× 449 1.0× 865 2.3× 604 1.9× 65 0.7× 50 1.4k
Jöerg Lehmann Australia 23 892 1.6× 1.1k 2.4× 893 2.4× 267 0.9× 102 1.0× 106 1.6k
Yi Le United States 13 169 0.3× 231 0.5× 207 0.5× 82 0.3× 68 0.7× 64 568
Frank M. Waterman United States 21 472 0.8× 1.0k 2.2× 983 2.6× 588 1.9× 168 1.7× 45 1.6k

Countries citing papers authored by Andrew Beavis

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Beavis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Beavis

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Beavis. A scholar is included among the top collaborators of Andrew Beavis 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 Andrew Beavis. Andrew Beavis 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
1.
Benoit, David M., et al.. (2024). Encoder-decoder convolutional neural network for simple CT segmentation of COVID-19 infected lungs. PeerJ Computer Science. 10. e2178–e2178. 1 indexed citations
2.
Benoit, David M., et al.. (2023). Evaluation of the dataset quality in gamma passing rate predictions using machine learning methods. British Journal of Radiology. 96(1147). 20220302–20220302. 1 indexed citations
3.
Li, Chun, et al.. (2022). Exploring hypoxic biology to improve radiotherapy outcomes. Expert Reviews in Molecular Medicine. 24. e21–e21. 13 indexed citations
4.
Renard, Isaline, Chun Li, Rajarshi Roy, et al.. (2021). PI3K inhibition as a novel therapeutic strategy for neoadjuvant chemoradiotherapy resistant oesophageal adenocarcinoma. British Journal of Radiology. 94(1119). 20201191–20201191. 2 indexed citations
5.
6.
Cole, A. L., et al.. (2016). Host innate inflammatory factors and staphylococcal protein A influence the duration of human Staphylococcus aureus nasal carriage. Mucosal Immunology. 9(6). 1537–1548. 29 indexed citations
7.
Moore, C S, et al.. (2015). Retrospective review of locally set tolerances for VMAT prostate patient specific QA using the COMPASS® system. Physica Medica. 31(7). 792–797. 12 indexed citations
8.
Moore, C S, et al.. (2015). Correlation between the signal-to-noise ratio improvement factor (KSNR) and clinical image quality for chest imaging with a computed radiography system. Physics in Medicine and Biology. 60(23). 9047–9058. 10 indexed citations
9.
Hingorani, Mohan, Sanjay Dixit, Miriam J. Johnson, et al.. (2015). Palliative Radiotherapy in the Presence of Well-Controlled Metastatic Disease after Initial Chemotherapy May Prolong Survival in Patients with Metastatic Esophageal and Gastric Cancer. Cancer Research and Treatment. 47(4). 706–717. 18 indexed citations
10.
Liney, Gary, et al.. (2013). Commissioning of a new wide-bore MRI scanner for radiotherapy planning of head and neck cancer. British Journal of Radiology. 86(1027). 20130150–20130150. 31 indexed citations
11.
Moore, C S, et al.. (2013). Correlation of the clinical and physical image quality in chest radiography for average adults with a computed radiography imaging system. British Journal of Radiology. 86(1027). 20130077–20130077. 31 indexed citations
12.
Beavis, Andrew & James W. Ward. (2012). WE‐G‐BRA‐04: The Development of a Virtual Reality Dosimetry Training Platform for Physics Training. Medical Physics. 39(6Part28). 3969–3969. 5 indexed citations
13.
Davis, A. W., et al.. (2011). Validation of a large-scale audit technique for CT dose optimisation. Radiation Protection Dosimetry. 150(4). 427–433. 9 indexed citations
14.
15.
Phillips, R. J., James W. Ward, Lindsay C. Page, et al.. (2008). Virtual reality training for radiotherapy becomes a reality.. PubMed. 132. 366–71. 19 indexed citations
16.
Ward, James W., et al.. (2007). Immersive visualization with automated collision detection for radiotherapy treatment planning.. PubMed. 125. 491–6. 10 indexed citations
17.
Beavis, Andrew, et al.. (2005). Re-treatment of a lung tumour using a simple intensity-modulated radiotherapy approach. British Journal of Radiology. 78(928). 358–361. 7 indexed citations
18.
Beavis, Andrew. (2004). Is tomotherapy the future of IMRT?. British Journal of Radiology. 77(916). 285–295. 97 indexed citations
19.
Markman, Jerry, Daniel A. Low, Andrew Beavis, & Joseph O. Deasy. (2002). Beyond bixels: Generalizing the optimization parameters for intensity modulated radiation therapy. Medical Physics. 29(10). 2298–2304. 13 indexed citations
20.
Beavis, Andrew. (1997). Implementation of Enhanced Dynamic Wedge into the Multidata DSS Radiotherapy Treatment Planning System. Medical dosimetry. 22(3). 219–225. 6 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Richard Canters Breakdown of academic impact, for papers by Michel Féron Breakdown of academic impact, for papers by Mika Kapanen Breakdown of academic impact, for papers by A. Tai Breakdown of academic impact, for papers by A Boyer Breakdown of academic impact, for papers by Matthew B. Podgorsak Breakdown of academic impact, for papers by Devon Godfrey Breakdown of academic impact, for papers by Jöerg Lehmann Breakdown of academic impact, for papers by Yi Le Breakdown of academic impact, for papers by Frank M. Waterman
Rankless by CCL
2026