MJ Michell

41 papers receiving 680 citations

Peers

MJ Michell
Comparison fields: 5 of 72
  • Pathology and Forensic Medicine 266
  • Cancer Research 164
  • Dermatology 79
  • Oncology 190
  • Radiology, Nuclear Medicine and Imaging 116
Replace L.J. Yeoman with:
L.J. Yeoman United Kingdom
Hiroko S. Tsunoda Japan
G. Stauch Germany
Michele B Drotman United States
Alfonso Frigerio Italy
CAROLINE M. E. RUBIN United Kingdom
Rita Bonardi Italy
Antuono Latronico Italy
Volker F. Duda Germany
Ann O’Doherty Ireland
MJ Michell relative to L.J. Yeoman United Kingdom L.J. Yeoman's profile →
Citations per field
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L.J. Yeoman · 1×
Citations per year

Countries citing papers authored by MJ Michell

Since Specialization
Citations

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

Fields of papers citing papers by MJ Michell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside MJ Michell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with MJ Michell Line = papers co-authored together MJ Michell links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010120
2 2009108
3 199388
4 199152
5 200039
6 200839
7 200032
8 199730
9 199124
10 199522
11 199518
12 199917
13 198916
14 199413
15 200112
16 201010
17 199610
18 199810
19 20069
20 20128

About MJ Michell

MJ Michell is a scholar working on Pathology and Forensic Medicine, Cancer Research, Radiology, Nuclear Medicine and Imaging, Oncology and Artificial Intelligence, having authored 44 papers that have together received 742 indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (17 papers), Breast Cancer Treatment Studies (14 papers), AI in cancer detection (12 papers), Global Cancer Incidence and Screening (11 papers), Digital Radiography and Breast Imaging (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Cancer and Skin Lesions (4 papers) and Colorectal Cancer Screening and Detection (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (266 citations), Cancer Research (164 citations), Dermatology (79 citations), Oncology (190 citations) and Radiology, Nuclear Medicine and Imaging (116 citations). MJ Michell has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include A.R.M. Wilson, Elizabeth A.M. O'Flynn, Stephen Humphreys, HEATHER B. NUNNERLEY, Fiona J. Gilbert, Robert L. Hayes, J Chamberlain, A.E. Kirkpatrick, Louise E. Johns and Anthony Maxwell. Their work appears in journals such as Clinical Radiology, Breast Cancer Research, The Breast, International Journal of Clinical Practice and British Journal of Radiology.

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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