Fábio Alexandre Spanhol
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Artificial Intelligence top 0.5%
- AI in cancer detection
Papers in
-
- IoT and Edge/Fog Computing 4
- Bluetooth and Wireless Communication Technologies 4
-
- Digital Imaging for Blood Diseases 3
- Co-authors
- Caroline Petitjean (4 shared papers)Luiz S. Oliveira (4 shared papers)Laurent Heutte (4 shared papers)Paulo Cavalin (1 shared paper)Paul Honeiné (1 shared paper)Leila Droprinchinski Martins (5 shared papers)Cléber Antônio Lindino (2 shared papers)Álvaro Largura (2 shared papers)
In The Last Decade
Fábio Alexandre Spanhol
16 papers receiving 2.3k citations
Fábio Alexandre Spanhol's Hit Papers
Peers
Comparison fields: 5 of 115
- Radiology, Nuclear Medicine and Imaging 1.3k
- Artificial Intelligence 2.0k
- Computer Vision and Pattern Recognition 1.2k
- Neurology 303
- Biophysics 124
Countries citing papers authored by Fábio Alexandre Spanhol
This map shows the geographic impact of Fábio Alexandre Spanhol'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 Fábio Alexandre Spanhol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fábio Alexandre Spanhol more than expected).
Fields of papers citing papers by Fábio Alexandre Spanhol
This network shows the impact of papers produced by Fábio Alexandre Spanhol. 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 Fábio Alexandre Spanhol. The network helps show where Fábio Alexandre Spanhol may publish in the future.
Co-authors
The 13 scholars most cited alongside Fábio Alexandre Spanhol, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A Dataset for Breast Cancer Histopathological Image Classification Hit paper breakdown → | 2015 | 1143 |
| 2 | Breast cancer histopathological image classification using Convolutional Neural Networks Hit paper breakdown → | 2016 | 630 |
| 3 | 2018 | 258 | |
| 4 | 2017 | 226 | |
| 5 | 2023 | 58 | |
| 6 | 2021 | 21 | |
| 7 | Gerenciamento de projetos | 2012 | 18 |
| 8 | 2009 | 13 | |
| 9 | Automatic breast cancer classification from histopathological images : a hybrid approach | 2018 | 7 |
| 10 | 2022 | 3 | |
| 11 | 2022 | 2 | |
| 12 | 2009 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2022 | 1 | |
| 15 | 2020 | 1 | |
| 16 | 2021 | 1 | |
| 17 | 2023 | 0 |
About Fábio Alexandre Spanhol
Fábio Alexandre Spanhol is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence, Environmental Engineering and Electrical and Electronic Engineering, having authored 17 papers that have together received 2.4k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (4 papers), Air Quality Monitoring and Forecasting (4 papers), AI in cancer detection (4 papers), IoT Networks and Protocols (4 papers), Bluetooth and Wireless Communication Technologies (4 papers), Digital Imaging for Blood Diseases (3 papers), Water Quality Monitoring Technologies (3 papers) and Vehicle emissions and performance (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.3k citations), Artificial Intelligence (2.0k citations), Computer Vision and Pattern Recognition (1.2k citations), Neurology (303 citations) and Biophysics (124 citations). Fábio Alexandre Spanhol has collaborated with scholars based in Brazil, France and Portugal. Frequent co-authors include Caroline Petitjean, Luiz S. Oliveira, Laurent Heutte, Paulo Cavalin, Paul Honeiné, Leila Droprinchinski Martins, Cléber Antônio Lindino, Álvaro Largura, Fabiano Sandrini and Leonor Gusmão. Their work appears in journals such as Forensic Science International Genetics, Environmental Monitoring and Assessment, Sensors, IEEE Transactions on Biomedical Engineering and Journal of Internet Services and Applications.
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.