Mark Brooks

948 total citations
10 papers, 658 citations indexed

About

Mark Brooks is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, Mark Brooks has authored 10 papers receiving a total of 658 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cardiology and Cardiovascular Medicine, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Neurology. Recurrent topics in Mark Brooks's work include Cardiac, Anesthesia and Surgical Outcomes (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Mark Brooks is often cited by papers focused on Cardiac, Anesthesia and Surgical Outcomes (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Mark Brooks collaborates with scholars based in Australia, United Kingdom and Ireland. Mark Brooks's co-authors include S Sarin, Ronil V. Chandra, Hong Kuan Kok, S Bann, Hamed Asadi, Shiwei Huang, Michael J. Lee, Guy Handelman, Amir H. Razavi and R. F. Slocombe and has published in prestigious journals such as British journal of surgery, American Journal of Roentgenology and British Journal of Radiology.

In The Last Decade

Mark Brooks

10 papers receiving 635 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark Brooks Australia	7	239	214	125	107	93	10	658
Elsie Ross United States	14	151 0.6×	227 1.1×	65 0.5×	104 1.0×	148 1.6×	41	657
Heewon Chung South Korea	17	226 0.9×	119 0.6×	356 2.8×	176 1.6×	121 1.3×	37	968
Fajin Dong China	15	148 0.6×	153 0.7×	335 2.7×	174 1.6×	117 1.3×	99	1.0k
Junhong Chen China	18	204 0.9×	145 0.7×	92 0.7×	79 0.7×	30 0.3×	59	737
Jens Meier Austria	21	170 0.7×	217 1.0×	72 0.6×	72 0.7×	190 2.0×	115	1.4k
Guy Handelman Ireland	5	91 0.4×	124 0.6×	189 1.5×	163 1.5×	158 1.7×	5	914
Amir H. Razavi Canada	7	71 0.3×	119 0.6×	183 1.5×	191 1.8×	124 1.3×	15	937
Xiaoying Yang China	9	244 1.0×	54 0.3×	123 1.0×	98 0.9×	55 0.6×	22	686
Mario Merone Italy	14	139 0.6×	52 0.2×	143 1.1×	132 1.2×	49 0.5×	72	690
Daniel S. Herman United States	14	183 0.8×	132 0.6×	45 0.4×	50 0.5×	38 0.4×	33	682

Countries citing papers authored by Mark Brooks

Since Specialization

Citations

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

Fields of papers citing papers by Mark Brooks

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Brooks

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

All Works

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10 of 10 papers shown

Kok, Hong Kuan, Christen Barras, Lee‐Anne Slater, et al.. (2024). Can artificial intelligence improve patient educational material readability? A systematic review and narrative synthesis. Internal Medicine Journal. 55(1). 20–34. 15 indexed citations

Ren, Yifan, Hong Kuan Kok, Paul D. Smith, et al.. (2024). Verification of a simplified aneurysm dimensionless flow parameter to predict intracranial aneurysm rupture status. British Journal of Radiology. 97(1159). 1357–1364. 1 indexed citations

Tahayori, Bahman, Hong Kuan Kok, Julian Maingard, et al.. (2023). Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging. European Radiology Experimental. 7(1). 17–17. 16 indexed citations

Tahayori, Bahman, Hong Kuan Kok, Julian Maingard, et al.. (2021). Review of deep learning algorithms for the automatic detection of intracranial hemorrhages on computed tomography head imaging. Journal of NeuroInterventional Surgery. 13(4). 369–378. 39 indexed citations

Handelman, Guy, Hong Kuan Kok, Ronil V. Chandra, et al.. (2018). Peering Into the Black Box of Artificial Intelligence: Evaluation Metrics of Machine Learning Methods. American Journal of Roentgenology. 212(1). 38–43. 269 indexed citations

Sardjono, Caroline T., Patricia L. Mottram, Maree S. Powell, et al.. (2005). Development of spontaneous multisystem autoimmune disease and hypersensitivity to antibody‐induced inflammation in Fcγ receptor IIa–transgenic mice. Arthritis & Rheumatism. 52(10). 3220–3229. 66 indexed citations

Brooks, Mark, et al.. (2005). Comparison of Surgical Risk Score, POSSUM and p-POSSUM in higher-risk surgical patients. British journal of surgery. 92(10). 1288–1292. 106 indexed citations

Bann, S, et al.. (2002). General Papers 15. British journal of surgery. 89(S1). 19–19. 2 indexed citations

Bann, S, et al.. (2002). Audit 07. British journal of surgery. 89(S1). 66–66. 1 indexed citations

10.

Bann, S, et al.. (2002). The surgical risk scale as an improved tool for risk-adjusted analysis in comparative surgical audit. British journal of surgery. 89(6). 763–768. 143 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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