Clare McGenity

818 total citations · 1 hit paper
10 papers, 107 citations indexed

About

Clare McGenity is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Epidemiology. According to data from OpenAlex, Clare McGenity has authored 10 papers receiving a total of 107 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Artificial Intelligence and 4 papers in Epidemiology. Recurrent topics in Clare McGenity's work include Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (5 papers) and Liver Disease Diagnosis and Treatment (4 papers). Clare McGenity is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (5 papers) and Liver Disease Diagnosis and Treatment (4 papers). Clare McGenity collaborates with scholars based in United Kingdom, Sweden and United States. Clare McGenity's co-authors include Darren Treanor, Gillian A. Matthews, Emily L. Clarke, Deborah Stocken, Patrick M. Bossuyt, Bethany Williams, Helmut Denk, K A Fleming, Robert Goldin and Kurt Zatloukal and has published in prestigious journals such as Scientific Reports, Journal of Hepatology and The Journal of Pathology.

In The Last Decade

Clare McGenity

8 papers receiving 104 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy

2024 67 citations Clare McGenity, Emily L. Clarke et al. npj Digital Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Clare McGenity United Kingdom	6	51	35	33	17	15	10	107
Maximilian Alber Germany	5	77 1.5×	52 1.5×	25 0.8×	30 1.8×	15 1.0×	13	159
Krishna Nand Keshava Murthy United States	5	35 0.7×	61 1.7×	47 1.4×	7 0.4×	20 1.3×	10	134
Ran Godrich United States	3	132 2.6×	103 2.9×	38 1.2×	26 1.5×	9 0.6×	5	180
Jeremy D. Kunz United States	3	132 2.6×	103 2.9×	38 1.2×	25 1.5×	9 0.6×	4	179
Piet Vercauter Belgium	5	21 0.4×	44 1.3×	30 0.9×	33 1.9×	7 0.5×	7	181
Keluo Yao United States	8	83 1.6×	52 1.5×	8 0.2×	25 1.5×	20 1.3×	14	135
Mustafa Nasir-Moin United States	5	63 1.2×	62 1.8×	17 0.5×	29 1.7×	4 0.3×	12	118
Adam Shephard United Kingdom	6	70 1.4×	63 1.8×	10 0.3×	10 0.6×	10 0.7×	11	128
Leonor Cerdá-Alberich Spain	6	21 0.4×	53 1.5×	19 0.6×	20 1.2×	4 0.3×	13	92
Jakob Vielhauer Germany	4	91 1.8×	48 1.4×	98 3.0×	7 0.4×	9 0.6×	9	229

Countries citing papers authored by Clare McGenity

Since Specialization

Citations

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

Fields of papers citing papers by Clare McGenity

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Clare McGenity

This figure shows the co-authorship network connecting the top 25 collaborators of Clare McGenity. A scholar is included among the top collaborators of Clare McGenity 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 Clare McGenity. Clare McGenity 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:

10 of 10 papers shown

1.

McGenity, Clare, et al.. (2025). Liver-Quant: Feature-based image analysis toolkit for automatic quantification of metabolic dysfunction-associated steatotic liver disease. Computers in Biology and Medicine. 190. 110049–110049. 3 indexed citations

2.

Wright, Alexander, et al.. (2024). Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology. Scientific Reports. 14(1). 30400–30400.

3.

McGenity, Clare, et al.. (2024). Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy. npj Digital Medicine. 7(1). 114–114. 67 indexed citations breakdown →

4.

Rowe, Ian, et al.. (2024). WED-254 The true diagnostic performance of magnetic resonance elastography for the detection of advanced fibrosis in metabolic dysfunction-associated steatotic liver disease exceeds the diagnostic performance of liver biopsy. Journal of Hepatology. 80. S530–S530.

5.

Matthews, Gillian A., et al.. (2024). Public evidence on AI products for digital pathology. npj Digital Medicine. 7(1). 300–300. 6 indexed citations

6.

Hutchinson, J. Ciaran, Jennifer Picarsic, Clare McGenity, et al.. (2024). Whole Slide Imaging, Artificial Intelligence, and Machine Learning in Pediatric and Perinatal Pathology: Current Status and Future Directions. Pediatric and Developmental Pathology. 28(2). 91–98. 6 indexed citations

7.

McGenity, Clare, Rebecca Randell, Christopher Bellamy, et al.. (2023). Survey of liver pathologists to assess attitudes towards digital pathology and artificial intelligence. Journal of Clinical Pathology. 77(1). 27–33. 5 indexed citations

8.

McGenity, Clare, Patrick M. Bossuyt, & Darren Treanor. (2022). Reporting of Artificial Intelligence Diagnostic Accuracy Studies in Pathology Abstracts: Compliance with STARD for Abstracts Guidelines. Journal of Pathology Informatics. 13. 100091–100091. 8 indexed citations

9.

Treanor, Darren, Clare McGenity, Jonathan R. Dillman, et al.. (2021). Improved pathology reporting in NAFLD/NASH for clinical trials. Journal of Clinical Pathology. 75(2). 73–75. 6 indexed citations

10.

McGenity, Clare & Darren Treanor. (2020). Guidelines for clinical trials using artificial intelligence – SPIRIT‐AI and CONSORT‐AI ^†. The Journal of Pathology. 253(1). 14–16. 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.

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