Adrián Colomer
Impact in
- Ophthalmology top 2%
- Glaucoma and retinal disorders
- Retinal Diseases and Treatments
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- Retinal Imaging and Analysis
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 23
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- Digital Imaging for Blood Diseases 12
- Medical Image Segmentation Techniques 5
- Co-authors
- Valery Naranjo (52 shared papers)Sandra Morales (6 shared papers)Julio Silva-Rodríguez (4 shared papers)Gabriel García (6 shared papers)Andres Diaz‐Pinto (1 shared paper)Yanwu Xu (1 shared paper)Rocío del Amor (13 shared papers)Alejandro F. Frangi (1 shared paper)
In The Last Decade
Adrián Colomer
52 papers receiving 760 citations
Peers
Comparison fields: 5 of 93
- Ophthalmology 226
- Radiology, Nuclear Medicine and Imaging 440
- Health Informatics 24
- Computer Vision and Pattern Recognition 293
- Artificial Intelligence 323
Countries citing papers authored by Adrián Colomer
This map shows the geographic impact of Adrián Colomer'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 Adrián Colomer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrián Colomer more than expected).
Fields of papers citing papers by Adrián Colomer
This network shows the impact of papers produced by Adrián Colomer. 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 Adrián Colomer. The network helps show where Adrián Colomer may publish in the future.
Co-authors
The 25 scholars most cited alongside Adrián Colomer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 148 | |
| 2 | 2020 | 84 | |
| 3 | 2020 | 61 | |
| 4 | 2015 | 57 | |
| 5 | 2020 | 37 | |
| 6 | 2021 | 30 | |
| 7 | 2020 | 29 | |
| 8 | 2021 | 27 | |
| 9 | 2019 | 26 | |
| 10 | 2021 | 23 | |
| 11 | 2020 | 21 | |
| 12 | 2021 | 19 | |
| 13 | 2021 | 19 | |
| 14 | 2023 | 16 | |
| 15 | 2019 | 15 | |
| 16 | 2022 | 15 | |
| 17 | 2020 | 15 | |
| 18 | 2022 | 15 | |
| 19 | 2021 | 10 | |
| 20 | 2017 | 10 |
About Adrián Colomer
Adrián Colomer is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oncology and Biomedical Engineering, having authored 56 papers that have together received 796 indexed citations. Recurring topics across this work include AI in cancer detection (23 papers), Retinal Imaging and Analysis (14 papers), Digital Imaging for Blood Diseases (12 papers), Cutaneous Melanoma Detection and Management (7 papers), Cell Image Analysis Techniques (6 papers), Glaucoma and retinal disorders (5 papers), Medical Image Segmentation Techniques (5 papers) and Medical Imaging and Analysis (5 papers). The work is most often cited by research in Ophthalmology (226 citations), Radiology, Nuclear Medicine and Imaging (440 citations), Health Informatics (24 citations), Computer Vision and Pattern Recognition (293 citations) and Artificial Intelligence (323 citations). Adrián Colomer has collaborated with scholars based in Spain, Norway and France. Frequent co-authors include Valery Naranjo, Sandra Morales, Julio Silva-Rodríguez, Gabriel García, Andres Diaz‐Pinto, Yanwu Xu, Rocío del Amor, Alejandro F. Frangi, Jorge Igual and Rafael Molina. Their work appears in journals such as Computer Methods and Programs in Biomedicine, IEEE Journal of Biomedical and Health Informatics, Scientific Reports, Histopathology and Applied Sciences.
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.