Guilherme Aresta
Impact in
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging
- Retinal Imaging and Analysis
- COVID-19 diagnosis using AI
Papers in
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- Retinal Imaging and Analysis 10
- Radiomics and Machine Learning in Medical Imaging 9
- COVID-19 diagnosis using AI 6
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- Retinal Diseases and Treatments 5
- Glaucoma and retinal disorders 3
- Co-authors
- Aurélio Campilho (13 shared papers)Teresa Araújo (12 shared papers)Paulo Aguiar (4 shared papers)Catarina Eloy (4 shared papers)António Polónia (4 shared papers)Eduardo Castro (1 shared paper)José Rouco (1 shared paper)Ana Maria Mendonc̨a (7 shared papers)
In The Last Decade
Guilherme Aresta
20 papers receiving 943 citations
Guilherme Aresta's Hit Papers
Peers
Comparison fields: 5 of 89
- Health Informatics 43
- Radiology, Nuclear Medicine and Imaging 681
- Artificial Intelligence 662
- Computer Vision and Pattern Recognition 336
- Health Information Management 62
Countries citing papers authored by Guilherme Aresta
This map shows the geographic impact of Guilherme Aresta'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 Guilherme Aresta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guilherme Aresta more than expected).
Fields of papers citing papers by Guilherme Aresta
This network shows the impact of papers produced by Guilherme Aresta. 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 Guilherme Aresta. The network helps show where Guilherme Aresta may publish in the future.
Co-authors
The 25 scholars most cited alongside Guilherme Aresta, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Classification of breast cancer histology images using Convolutional Neural Networks Hit paper breakdown → | 2017 | 648 |
| 2 | 2020 | 95 | |
| 3 | 2020 | 43 | |
| 4 | 2022 | 25 | |
| 5 | 2019 | 25 | |
| 6 | 2018 | 24 | |
| 7 | 2020 | 22 | |
| 8 | 2022 | 19 | |
| 9 | 2017 | 16 | |
| 10 | 2020 | 15 | |
| 11 | 2016 | 14 | |
| 12 | 2023 | 9 | |
| 13 | 2022 | 5 | |
| 14 | 2024 | 4 | |
| 15 | 2019 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2025 | 2 | |
| 19 | 2018 | 2 | |
| 20 | 2022 | 1 |
About Guilherme Aresta
Guilherme Aresta is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology, Artificial Intelligence, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 979 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (7 papers), Lung Cancer Diagnosis and Treatment (6 papers), COVID-19 diagnosis using AI (6 papers), Retinal Diseases and Treatments (5 papers), Digital Imaging for Blood Diseases (4 papers) and Glaucoma and retinal disorders (3 papers). The work is most often cited by research in Health Informatics (43 citations), Radiology, Nuclear Medicine and Imaging (681 citations), Artificial Intelligence (662 citations), Computer Vision and Pattern Recognition (336 citations) and Health Information Management (62 citations). Guilherme Aresta has collaborated with scholars based in Portugal, Austria and Iran. Frequent co-authors include Aurélio Campilho, Teresa Araújo, Paulo Aguiar, Catarina Eloy, António Polónia, Eduardo Castro, José Rouco, Ana Maria Mendonc̨a, Susana Penas and Luís Mendonça. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Scientific Reports, IEEE Access, Translational Vision Science & Technology and Computer Methods and Programs in Biomedicine.
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.