Eduardo Castro
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Neurology top 10%
- Oncology
- Co-authors
- Guilherme ArestaCatarina EloyAntónio PolóniaJosé RoucoPaulo AguiarTeresa AraújoAurélio CampilhoJaime S. Cardoso
- Topics
- AI in cancer detection (5 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Digital Imaging for Blood Diseases (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEMedical Image Analysis
- Partner nations
- PortugalUnited StatesUnited Kingdom
In The Last Decade
Eduardo Castro
9 papers receiving 701 citations
Hit Papers
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 601
- Radiology, Nuclear Medicine and Imaging 458
- Computer Vision and Pattern Recognition 300
- Neurology 91
- Oncology 76
Countries citing papers authored by Eduardo Castro
This map shows the geographic impact of Eduardo Castro'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 Eduardo Castro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eduardo Castro more than expected).
Fields of papers citing papers by Eduardo Castro
This network shows the impact of papers produced by Eduardo Castro. 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 Eduardo Castro. The network helps show where Eduardo Castro may publish in the future.
Co-authorship network of co-authors of Eduardo Castro
This figure shows the co-authorship network connecting the top 25 collaborators of Eduardo Castro. A scholar is included among the top collaborators of Eduardo Castro 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 Eduardo Castro. Eduardo Castro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 59 | |
| 10 | Classification of breast cancer histology images using Convolutional Neural Networksbreakdown → | 648 |
About Eduardo Castro
Eduardo Castro is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering and Artificial Intelligence, having authored 10 papers that have together received 728 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Digital Imaging for Blood Diseases (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (458 citations), Artificial Intelligence (601 citations) and Health Informatics (21 citations). Eduardo Castro has collaborated with scholars based in Portugal, United States and United Kingdom. Frequent co-authors include Guilherme Aresta, Catarina Eloy, António Polónia, José Rouco, Paulo Aguiar, Teresa Araújo, Aurélio Campilho, Jaime S. Cardoso, José Costa Pereira and Maria João Cardoso. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Medical Image Analysis.
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.