Andrew Scarsbrook

4.9k total citations
164 papers, 3.1k citations indexed

About

Andrew Scarsbrook is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Andrew Scarsbrook has authored 164 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Radiology, Nuclear Medicine and Imaging, 50 papers in Pulmonary and Respiratory Medicine and 37 papers in Surgery. Recurrent topics in Andrew Scarsbrook's work include Radiomics and Machine Learning in Medical Imaging (65 papers), Medical Imaging Techniques and Applications (48 papers) and Head and Neck Cancer Studies (18 papers). Andrew Scarsbrook is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (65 papers), Medical Imaging Techniques and Applications (48 papers) and Head and Neck Cancer Studies (18 papers). Andrew Scarsbrook collaborates with scholars based in United Kingdom, Netherlands and United States. Andrew Scarsbrook's co-authors include F.U. Chowdhury, Chirag N. Patel, Sriram Vaidyanathan, Robin Prestwich, Richard Graham, Kevin M. Bradley, Russell Frood, Fergus Gleeson, Chirag Patel and Mark Lansdown and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Endocrine Reviews.

In The Last Decade

Andrew Scarsbrook

151 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrew Scarsbrook United Kingdom	31	1.4k	901	890	567	341	164	3.1k
Venkatesh Rangarajan India	23	805 0.6×	1.2k 1.3×	710 0.8×	605 1.1×	223 0.7×	246	2.6k
Bart de Keizer Netherlands	35	1.4k 1.0×	1.0k 1.1×	1.1k 1.3×	708 1.2×	431 1.3×	158	3.5k
Pierre‐Yves Salaün France	27	1.2k 0.8×	568 0.6×	493 0.6×	328 0.6×	177 0.5×	175	2.5k
Zohar Keidar Israel	37	2.3k 1.6×	1.3k 1.5×	1.3k 1.5×	682 1.2×	671 2.0×	128	4.5k
Hidetake Yabuuchi Japan	31	1.9k 1.3×	797 0.9×	854 1.0×	312 0.6×	269 0.8×	168	3.5k
Francesco Giammarile France	35	1.6k 1.1×	884 1.0×	1.2k 1.4×	1.3k 2.3×	1.1k 3.2×	178	4.5k
Mathias Bressel Australia	35	1.0k 0.7×	1.7k 1.9×	789 0.9×	1.4k 2.4×	209 0.6×	184	3.8k
Hilmar Kuehl Germany	30	1.7k 1.2×	1.3k 1.4×	604 0.7×	689 1.2×	400 1.2×	57	3.1k
Naofumi Hayabuchi Japan	36	1.4k 1.0×	2.2k 2.5×	1.3k 1.5×	583 1.0×	634 1.9×	208	4.8k
Eric Rohren United States	35	2.2k 1.6×	1.6k 1.7×	885 1.0×	1.1k 1.9×	237 0.7×	132	4.4k

Countries citing papers authored by Andrew Scarsbrook

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Scarsbrook

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Scarsbrook

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

Cairns, James, Russell Frood, Chirag Patel, & Andrew Scarsbrook. (2025). The Role of AI in Lymphoma: An Update. Seminars in Nuclear Medicine. 55(3). 377–386. 3 indexed citations

Marco, Gabriele De, Katya Meridor, Tom Macleod, et al.. (2025). Late‐Onset Spondyloarthritis Presenting as Glucocorticoid‐Resistant Polymyalgia Rheumatica: A Hitherto Underappreciated Entity in Which Tumor Necrosis Factor or Interleukin ‐17 Blockade May Have a Therapeutic Role. Arthritis & Rheumatology. 78(1). 131–140.

Ravikumar, Nishant, et al.. (2025). A Methodological Framework for AI-Assisted Diagnosis of Ovarian Masses Using CT and MR Imaging. Journal of Personalized Medicine. 15(2). 76–76. 2 indexed citations

Frood, Russell, et al.. (2024). A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease. Tomography. 10(9). 1455–1487. 3 indexed citations

Frood, Russell, et al.. (2024). Prediction of Patient Outcomes in Locally Advanced Cervical Carcinoma Following Chemoradiotherapy—Comparative Effectiveness of Magnetic Resonance Imaging and 2-Deoxy-2-[18F]fluoro-D-glucose Imaging. Cancers. 16(3). 476–476. 1 indexed citations

Fatania, Kavi, Russell Frood, Hitesh Mistry, et al.. (2024). Tumour Size and Overall Survival in a Cohort of Patients with Unifocal Glioblastoma: A Uni- and Multivariable Prognostic Modelling and Resampling Study. Cancers. 16(7). 1301–1301.

Frood, Russell, et al.. (2024). Can Patient Characteristics and Pre-Treatment MRI Features Predict Survival After Stereotactic Ablative Radiotherapy (SABR) Treatment in Hepatocellular Carcinoma (HCC): Preliminary Assessment. Current Oncology. 31(10). 6384–6394. 1 indexed citations

Gilbert, Alexandra, J. Lilley, Moloud Abdar, et al.. (2023). Toxicity Prediction in Pelvic Radiotherapy Using Multiple Instance Learning and Cascaded Attention Layers. IEEE Journal of Biomedical and Health Informatics. 27(4). 1958–1966. 2 indexed citations

Frood, Russell, et al.. (2023). Clinical Utility of Second-Look FDG PET-CT to Stratify Incomplete Metabolic Response Post (Chemo) Radiotherapy in Oropharyngeal Squamous Cell Carcinoma. Cancers. 15(2). 464–464. 1 indexed citations

10.

Allen, Katrina J., et al.. (2023). Artificial intelligence in ovarian cancer histopathology: a systematic review. npj Precision Oncology. 7(1). 83–83. 33 indexed citations

11.

Payne, Heather, et al.. (2022). White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 2 indexed citations

12.

Frood, Russell, et al.. (2022). Accuracy of Response Assessment FDG PET-CT Post (Chemo)Radiotherapy in HPV Negative Oropharynx Squamous Cell Carcinoma. Cancers. 14(19). 4680–4680. 1 indexed citations

13.

Zhong, Jim, Sarah Brown, Maria Aparecida Alves de Oliveira Serra, et al.. (2022). Reirradiation Options for Previously Irradiated Prostate cancer (RO-PIP): Feasibility study investigating toxicity outcomes following reirradiation with stereotactic body radiotherapy (SBRT) versus high-dose-rate brachytherapy (HDR-BT). BMJ Open. 12(11). e068580–e068580. 5 indexed citations

14.

Harrison, Stephanie R, et al.. (2021). Chest pain mimicking pulmonary embolism may be a common presentation of COVID‐19 in ambulant patients without other typical features of infection. Journal of Internal Medicine. 290(2). 349–358. 6 indexed citations

15.

Slevin, Finbar, Matthew Beasley, William Cross, et al.. (2020). Patterns of Lymph Node Failure in Patients With Recurrent Prostate Cancer Postradical Prostatectomy and Implications for Salvage Therapies. Advances in Radiation Oncology. 5(6). 1126–1140. 6 indexed citations

16.

Sherlock, Mark, Andrew Scarsbrook, Afroze Abbas, et al.. (2020). Adrenal Incidentaloma. Endocrine Reviews. 41(6). 775–820. 164 indexed citations

17.

McDermott, Garry, et al.. (2019). Protocol-driven multidetector SPECT/CT: integration of hybrid imaging into the routine workflow of whole-body bone scintigraphy in oncology patients. Clinical Radiology. 75(1). 79.e1–79.e7. 2 indexed citations

18.

Murray, Louise, et al.. (2019). Incidence and patterns of retropharyngeal lymph node involvement in oropharyngeal carcinoma. Radiotherapy and Oncology. 142. 92–99. 15 indexed citations

19.

Scarsbrook, Andrew, Gillian Ward, Karen Marshall, et al.. (2017). Respiratory-gated (4D) contrast-enhanced FDG PET-CT for radiotherapy planning of lower oesophageal carcinoma: feasibility and impact on planning target volume. BMC Cancer. 17(1). 671–671. 8 indexed citations

20.

Scarsbrook, Andrew, Sriram Vaidyanathan, F.U. Chowdhury, et al.. (2016). Efficacy of qualitative response assessment interpretation criteria at 18F-FDG PET-CT for predicting outcome in locally advanced cervical carcinoma treated with chemoradiotherapy. European Journal of Nuclear Medicine and Molecular Imaging. 44(4). 581–588. 22 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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