Pedro Morais
Impact in
- Health Informatics top 10%
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- Cardiac Imaging and Diagnostics
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Cardiac Valve Diseases and Treatments 11
- Atrial Fibrillation Management and Outcomes 7
- Co-authors
- João L. Vilaça (78 shared papers)Sandro Queirós (30 shared papers)Jan D’hooge (23 shared papers)Jaime C. Fonseca (31 shared papers)Bruno Oliveira (36 shared papers)Helena R. Torres (36 shared papers)Brecht Heyde (3 shared papers)Daniel Barbosa (7 shared papers)
In The Last Decade
Pedro Morais
79 papers receiving 959 citations
Peers
Comparison fields: 5 of 111
- Health Informatics 19
- Radiology, Nuclear Medicine and Imaging 266
- Cardiology and Cardiovascular Medicine 249
- Computer Vision and Pattern Recognition 211
- Orthopedics and Sports Medicine 66
Countries citing papers authored by Pedro Morais
This map shows the geographic impact of Pedro Morais'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 Pedro Morais with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro Morais more than expected).
Fields of papers citing papers by Pedro Morais
This network shows the impact of papers produced by Pedro Morais. 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 Pedro Morais. The network helps show where Pedro Morais may publish in the future.
Co-authors
The 25 scholars most cited alongside Pedro Morais, 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 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 110 | |
| 2 | 2016 | 79 | |
| 3 | 2018 | 73 | |
| 4 | 2008 | 56 | |
| 5 | 2022 | 48 | |
| 6 | 2010 | 38 | |
| 7 | 2022 | 36 | |
| 8 | 2018 | 30 | |
| 9 | 2018 | 27 | |
| 10 | 2016 | 25 | |
| 11 | 2018 | 22 | |
| 12 | 2017 | 21 | |
| 13 | 2013 | 20 | |
| 14 | 2017 | 18 | |
| 15 | 2018 | 18 | |
| 16 | 2023 | 17 | |
| 17 | 2023 | 17 | |
| 18 | 2016 | 17 | |
| 19 | 2018 | 16 | |
| 20 | 2017 | 16 |
About Pedro Morais
Pedro Morais is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Surgery, having authored 88 papers that have together received 977 indexed citations. Recurring topics across this work include Cardiac Valve Diseases and Treatments (11 papers), Medical Image Segmentation Techniques (9 papers), AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Surgical Simulation and Training (7 papers), Atrial Fibrillation Management and Outcomes (7 papers), Craniofacial Disorders and Treatments (7 papers) and Advanced Neural Network Applications (6 papers). The work is most often cited by research in Health Informatics (19 citations), Radiology, Nuclear Medicine and Imaging (266 citations), Cardiology and Cardiovascular Medicine (249 citations), Computer Vision and Pattern Recognition (211 citations) and Orthopedics and Sports Medicine (66 citations). Pedro Morais has collaborated with scholars based in Portugal, Belgium and Germany. Frequent co-authors include João L. Vilaça, Sandro Queirós, Jan D’hooge, Jaime C. Fonseca, Bruno Oliveira, Helena R. Torres, Brecht Heyde, Daniel Barbosa, Fernando Veloso and Denis Friboulet. Their work appears in journals such as Sensors, Medical Physics, Medical Image Analysis, International Journal for Numerical Methods in Biomedical Engineering 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.