Fernando Collado‐Mesa

1.2k citations
40 papers · 802 indexed · h-index 14
Topics
Radiomics and Machine Learning in Medical Imaging (8 papers)AI in cancer detection (8 papers)Breast Cancer Treatment Studies (6 papers)
Journals
SHILAP Revista de lepidopterologíaDiabetes CareEuropean Heart Journal

In The Last Decade

Fernando Collado‐Mesa

38 papers receiving 767 citations

Peers

Fernando Collado‐Mesa
Comparison fields: 5 of 129
  • Radiology, Nuclear Medicine and Imaging 243
  • Artificial Intelligence 182
  • Oncology 151
  • Dermatology 138
  • Health Informatics 97
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Citations per field
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Citations per year

Countries citing papers authored by Fernando Collado‐Mesa

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Collado‐Mesa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Collado‐Mesa. 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 Fernando Collado‐Mesa. The network helps show where Fernando Collado‐Mesa may publish in the future.

Co-authorship network of co-authors of Fernando Collado‐Mesa

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 2
3 2
4 2
5 15
6 52
7 116
8 97
9 9
10 1
11 8
12 29
13 20
14 10
15 1
16 89
17 13
18 52
19
Mortalidad en diabéticos insulinodependientes: Ciudad de La Habana, 1965-1991
0
20
Seroprevalencia del virus de la hepatitis C en diferentes grupos de población y factores de riesgo asociados: Cuba, 1991
2

About Fernando Collado‐Mesa

Fernando Collado‐Mesa is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Dermatology, having authored 40 papers that have together received 802 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), AI in cancer detection (8 papers) and Breast Cancer Treatment Studies (6 papers). The work is most often cited by research in Health Informatics (97 citations), Dermatology (138 citations) and Radiology, Nuclear Medicine and Imaging (243 citations). Fernando Collado‐Mesa has collaborated with scholars based in United States, Saudi Arabia and Cuba. Frequent co-authors include Manal Alghamdi, Mohamed Abdel-Mottaleb, Shasa Hu, Fangchao Ma, Robert S. Kirsner, Kris Arheart, Monica Yepes, Jose Net, Kristopher L. Arheart and Robert S. Kirsner. Their work appears in journals such as SHILAP Revista de lepidopterología, Diabetes Care and European Heart Journal.

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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