F. Mayall

1.6k citations
41 papers · 781 · h-index 18

Impact in

Papers in

F. Mayall

39 papers receiving 704 citations

Peers

F. Mayall
Comparison fields: 5 of 64
  • Pulmonary and Respiratory Medicine 377
  • Obstetrics and Gynecology 67
  • Pathology and Forensic Medicine 122
  • Oncology 169
  • Rheumatology 87
Replace Toshiaki Kamei with:
Toshiaki Kamei Japan
Noel F. Quenville Canada
V. Wadehra United Kingdom
Kimiya Sato Japan
Suk Jin Choi South Korea
Seung Yeon Ha South Korea
Farnaz Hasteh United States
Donald A. Elmajian United States
Sang‐Woo Juhng South Korea
Adele Fornelli Italy
F. Mayall relative to Toshiaki Kamei Japan Toshiaki Kamei's profile →
Citations per field
00.5×6.7×
Toshiaki Kamei · 1×
Citations per year

Countries citing papers authored by F. Mayall

Since Specialization
Citations

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

Fields of papers citing papers by F. Mayall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside F. Mayall, 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 F. Mayall Line = papers co-authored together F. Mayall links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199478
2 199267
3 199256
4 200342
5 199242
6 199741
7 199936
8 200036
9 200328
10 199923
11 199723
12 199322
13 199821
14 199218
15 199618
16 201018
17 199818
18 199117
19 199417
20 201317

About F. Mayall

F. Mayall is a scholar working on Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine, Oncology, Dermatology and Surgery, having authored 41 papers that have together received 781 indexed citations. Recurring topics across this work include Occupational and environmental lung diseases (11 papers), Sarcoma Diagnosis and Treatment (4 papers), Breast Lesions and Carcinomas (3 papers), Lymphoma Diagnosis and Treatment (3 papers), Endometriosis Research and Treatment (2 papers), Neuroblastoma Research and Treatments (2 papers), Cancer-related Molecular Pathways (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (377 citations), Obstetrics and Gynecology (67 citations), Pathology and Forensic Medicine (122 citations), Oncology (169 citations) and Rheumatology (87 citations). F. Mayall has collaborated with scholars based in United Kingdom, New Zealand and United States. Frequent co-authors include A R Gibbs, Brent A. Chang, Fiona Campbell, Gregory M. Jacobson, B J Harrison, R W Blewitt, A Heryet, Joy Hickman, Robert J. Nicholls and Michael Dray. Their work appears in journals such as Journal of Clinical Pathology, Histopathology, Cytopathology, The Journal of Pathology and The Journal of Laryngology & Otology.

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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