Carmen Serrano

61 papers receiving 1.2k citations

Peers

Carmen Serrano
Comparison fields: 5 of 120
  • Occupational Therapy 101
  • Rehabilitation 134
  • Cognitive Neuroscience 187
  • Oncology 243
  • Computer Vision and Pattern Recognition 189
Replace Begoña Acha with:
Begoña Acha Spain
Karl Thurnhofer‐Hemsi Spain
Samuel Ortega Spain
Ewa Piętka Poland
Suman Tewary India
Yulin Wang China
Rosalind Pratt United Kingdom
Ebrahim Mohammed Senan Saudi Arabia
Konstantinos Sirlantzis United Kingdom
Wenjun Tan China
Carmen Serrano relative to Begoña Acha Spain Begoña Acha's profile →
Citations per field
00.5×1.5×
Begoña Acha · 1×
Citations per year

Countries citing papers authored by Carmen Serrano

Since Specialization
Citations

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

Fields of papers citing papers by Carmen Serrano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Carmen Serrano, 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 Carmen Serrano Line = papers co-authored together Carmen Serrano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013232
2 201284
3 201463
4 200860
5 199954
6 200854
7 200549
8 201544
9 200542
10 201241
11 201341
12 201129
13 201026
14 201622
15 200921
16 201121
17 201318
18 200318
19 200417
20 202216

About Carmen Serrano

Carmen Serrano is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oncology, Artificial Intelligence and Rehabilitation, having authored 62 papers that have together received 1.2k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (9 papers), Medical Image Segmentation Techniques (9 papers), Cutaneous Melanoma Detection and Management (8 papers), Wound Healing and Treatments (7 papers), Advanced Memory and Neural Computing (6 papers), Advanced Data Compression Techniques (6 papers), melanin and skin pigmentation (5 papers) and AI in cancer detection (5 papers). The work is most often cited by research in Occupational Therapy (101 citations), Rehabilitation (134 citations), Cognitive Neuroscience (187 citations), Oncology (243 citations) and Computer Vision and Pattern Recognition (189 citations). Carmen Serrano has collaborated with scholars based in Spain, Canada and United States. Frequent co-authors include Begoña Acha, Tomás Gómez‐Cía, J. A. Pérez‐Carrasco, Laura M. Roa, B. Linares-Barranco, Teresa Serrano‐Gotarredona, Irene Fondón, Aurora Sáez, Shouchun Chen and Bo Zhao. Their work appears in journals such as Burns, Machine Vision and Applications, International Journal of Computer Assisted Radiology and Surgery, Journal of Biomedical Optics and IEEE Transactions on Medical Imaging.

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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