Matthew Williams

3.0k total citations
72 papers, 1.1k citations indexed

About

Matthew Williams is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Matthew Williams has authored 72 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Genetics, 17 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Matthew Williams's work include Glioma Diagnosis and Treatment (17 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Brain Metastases and Treatment (8 papers). Matthew Williams is often cited by papers focused on Glioma Diagnosis and Treatment (17 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Brain Metastases and Treatment (8 papers). Matthew Williams collaborates with scholars based in United Kingdom, United States and China. Matthew Williams's co-authors include Anthony Hunter, Andrew Brodbelt, David Greenberg, V. Peter Collins, Sally Vernon, H. V. Smith, Thomas C. Booth, Haris Shuaib, M. Jorge Cardoso and K. Ashkan and has published in prestigious journals such as PLoS ONE, Brain and Cancer.

In The Last Decade

Matthew Williams

69 papers receiving 1.1k citations

Peers

Matthew Williams

GENET

RNMI

EPIDE

Todd Hollon United States

Florian Putz Germany

Mariam Aboian United States

Peter McLaren Black United States

Andrew D. Trister United States

Yimei Li United States

Phedias Diamandis Canada

Ian D. Connolly United States

Pamela S. Jones United States

Georg Göbel Austria

Todd Hollon United States

Matthew Williams

215 ×0.8

GENET

160 ×0.9

141 ×0.8

RNMI

55 ×0.4

155 ×1.0

EPIDE

Citations per year, relative to Matthew Williams Matthew Williams (= 1×) peers Todd Hollon

Countries citing papers authored by Matthew Williams

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Williams

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Islam, Syed, Marianna Inglese, Tara Barwick, et al.. (2025). A hybrid [18F]fluoropivalate PET-multiparametric MRI to detect and characterise brain tumour metastases based on a permissive environment for monocarboxylate transport. European Journal of Nuclear Medicine and Molecular Imaging. 52(7). 2290–2306. 1 indexed citations

Treasure, Peter, Thomas C. Booth, Stephen J. Price, et al.. (2025). Adult glioblastoma in England: Incidence, treatment, and outcomes with novel population-based strata. Cancer Epidemiology. 97. 102811–102811.

Williams, Matthew, et al.. (2024). ‘Lock them up and throw away the key’: an evaluation of the structure of punitive attitudes. Psychiatry Psychology and Law. 32(2). 213–239. 1 indexed citations

Williams, Matthew, et al.. (2023). Co-curricular Immersion as a Public–Private Capacity Building Activity. PubMed. 3(2). 165–178. 1 indexed citations

Mistry, Sanjay, et al.. (2023). Triaxial accelerometer-measured physical activity and functional behaviours among people with High Grade Glioma: The BrainWear Study. PLoS ONE. 18(5). e0285399–e0285399. 3 indexed citations

Davis, Charles H., Rohitashwa Sinha, Samantha J. Mills, et al.. (2022). Tumour treating fields in glioblastoma: is the treatment tolerable, effective, and practical in UK patients?. British Journal of Neurosurgery. 36(6). 770–776. 8 indexed citations

Plaha, Puneet, Sophie Camp, Jonathan Cook, et al.. (2022). FUTURE-GB: functional and ultrasound-guided resection of glioblastoma – a two-stage randomised control trial. BMJ Open. 12(11). e064823–e064823. 12 indexed citations

Chen, Jiarong, et al.. (2022). Improving on whole-brain radiotherapy in patients with large brain metastases: A planning study to support the AROMA clinical trial. Radiotherapy and Oncology. 170. 176–183. 5 indexed citations

Williams, Matthew, et al.. (2021). Exploring definitions of radiological sarcopenia in cancer: a protocol for a scoping review. BMJ Open. 11(7). e053076–e053076. 4 indexed citations

10.

Williams, Matthew, et al.. (2021). Registries, Databases and Repositories for Developing Artificial Intelligence in Cancer Care. Clinical Oncology. 34(2). e97–e103. 4 indexed citations

11.

Chen, Jiarong, et al.. (2021). Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma. British Journal of Cancer. 126(2). 196–203. 19 indexed citations

12.

Williams, Matthew, et al.. (2020). Estimating the Risk of Death from COVID-19 in Adult Cancer Patients. Clinical Oncology. 33(3). e172–e179. 13 indexed citations

13.

Brown, Nicholas F., Matthew Williams, Hendrik‐Tobias Arkenau, et al.. (2018). A study of the focal adhesion kinase inhibitor GSK2256098 in patients with recurrent glioblastoma with evaluation of tumor penetration of [11C]GSK2256098. Neuro-Oncology. 20(12). 1634–1642. 54 indexed citations

14.

Fan, Xiuyi, et al.. (2014). Dialogical two-agent decision making with assumption-based argumentation. Adaptive Agents and Multi-Agents Systems. 533–540. 20 indexed citations

15.

Savage, Philip, Rachel Sharkey, Lyn Schofield, et al.. (2013). Malignant spinal cord compression: NICE guidance, improvements and challenges. QJM. 107(4). 277–282. 35 indexed citations

16.

Williams, Matthew, David Woolf, John Dickson, Robert Hughes, & JaneMaree Maher. (2013). Routine Clinical Data Predict Survival after Palliative Radiotherapy: An Opportunity to Improve End of Life Care. Clinical Oncology. 25(11). 668–673. 10 indexed citations

17.

Craven, Robert, et al.. (2012). Efficient argumentation for medical decision-making. Principles of Knowledge Representation and Reasoning. 598–602. 11 indexed citations

18.

Williams, Matthew, et al.. (2012). Change in platelet levels during radiotherapy with concurrent and adjuvant temozolomide for the treatment of glioblastoma: a novel prognostic factor for survival. Journal of Cancer Research and Clinical Oncology. 138(10). 1683–1688. 20 indexed citations

19.

Fox, John, Elizabeth Black, David Glasspool, et al.. (2006). Towards a General Model for Argumentation Services.. Research Portal (King's College London). 52–57. 5 indexed citations

20.

Williams, Matthew, Balasubramanian Krishnan, J. David Clark, et al.. (2002). CORRECTION. Archives of Disease in Childhood. 87(5). 453–453. 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.

Explore authors with similar magnitude of impact