Felipe André Zeiser
Impact in
- Medical Laboratory Technology top 10%
Papers in
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- AI in cancer detection 4
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- Radiomics and Machine Learning in Medical Imaging 4
- COVID-19 diagnosis using AI 1
- Co-authors
- Cristiano André da Costa (12 shared papers)Rodrigo da Rosa Righi (8 shared papers)Gabriel de Oliveira Ramos (8 shared papers)Tiago Zonta (2 shared papers)Adriana Vial Roehe (3 shared papers)Nuno C. Marques (2 shared papers)Rafael Kunst (1 shared paper)Ismael Santos (3 shared papers)
In The Last Decade
Felipe André Zeiser
12 papers receiving 240 citations
Peers
Comparison fields: 5 of 78
- Medical Laboratory Technology 9
- Industrial and Manufacturing Engineering 30
- Neurology 25
- Artificial Intelligence 90
- Modeling and Simulation 13
Countries citing papers authored by Felipe André Zeiser
This map shows the geographic impact of Felipe André Zeiser'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 Felipe André Zeiser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felipe André Zeiser more than expected).
Fields of papers citing papers by Felipe André Zeiser
This network shows the impact of papers produced by Felipe André Zeiser. 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 Felipe André Zeiser. The network helps show where Felipe André Zeiser may publish in the future.
Co-authors
The 23 scholars most cited alongside Felipe André Zeiser, 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 | 2021 | 62 | |
| 2 | 2022 | 61 | |
| 3 | 2020 | 55 | |
| 4 | 2021 | 27 | |
| 5 | 2021 | 17 | |
| 6 | 2023 | 11 | |
| 7 | 2024 | 5 | |
| 8 | 2022 | 5 | |
| 9 | 2023 | 4 | |
| 10 | 2021 | 2 | |
| 11 | 2023 | 1 | |
| 12 | 2021 | 1 | |
| 13 | 2023 | 0 |
About Felipe André Zeiser
Felipe André Zeiser is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Molecular Biology and Information Systems, having authored 13 papers that have together received 251 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), COVID-19 diagnosis using AI (1 paper), Industrial Vision Systems and Defect Detection (1 paper), Image Retrieval and Classification Techniques (1 paper), Blockchain Technology Applications and Security (1 paper), Context-Aware Activity Recognition Systems (1 paper) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Medical Laboratory Technology (9 citations), Industrial and Manufacturing Engineering (30 citations), Neurology (25 citations), Artificial Intelligence (90 citations) and Modeling and Simulation (13 citations). Felipe André Zeiser has collaborated with scholars based in Brazil, Germany and Portugal. Frequent co-authors include Cristiano André da Costa, Rodrigo da Rosa Righi, Gabriel de Oliveira Ramos, Tiago Zonta, Adriana Vial Roehe, Nuno C. Marques, Rafael Kunst, Ismael Santos, Marcelo Moreno and Nêmora Tregnago Barcellos. Their work appears in journals such as Expert Systems with Applications, Computers & Geosciences, Journal of Digital Imaging, Applied Soft Computing and The Lancet Regional Health - Americas.
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.