Pedro Henriques Abreu

74 papers receiving 1.7k citations

Hit Papers

Cross-Validation for Imbalanced Datasets: Avoiding Overop...2018202620202023201850100150200250

Peers

Pedro Henriques Abreu
Comparison fields: 5 of 172
  • Artificial Intelligence 895
  • Radiology, Nuclear Medicine and Imaging 270
  • Computer Vision and Pattern Recognition 175
  • Health Information Management 153
  • Signal Processing 149
Replace José M. Jerez with:
José M. Jerez Spain
Eyad Elyan United Kingdom
Dharmendra Singh Rajput India
Firuz Kamalov United Arab Emirates
Mamta Mittal India
Buyue Qian United States
Jyotir Moy Chatterjee India
Mohamed Hammad Egypt
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Citations per field
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Citations per year

Countries citing papers authored by Pedro Henriques Abreu

Since Specialization
Citations

This map shows the geographic impact of Pedro Henriques Abreu'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 Henriques Abreu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro Henriques Abreu more than expected).

Fields of papers citing papers by Pedro Henriques Abreu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pedro Henriques Abreu. 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 Henriques Abreu. The network helps show where Pedro Henriques Abreu may publish in the future.

Co-authorship network of co-authors of Pedro Henriques Abreu

This figure shows the co-authorship network connecting the top 25 collaborators of Pedro Henriques Abreu. A scholar is included among the top collaborators of Pedro Henriques Abreu 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 Pedro Henriques Abreu. Pedro Henriques Abreu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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11 70
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Missing Image Data Imputation using Variational Autoencoders with Weighted Loss.
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17 59
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Interpreting deep learning models for ordinal problems.
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Knowledge representation in soccer domain: An ontology development
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About Pedro Henriques Abreu

Pedro Henriques Abreu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 82 papers that have together received 1.7k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (11 papers), Imbalanced Data Classification Techniques (9 papers) and AI in cancer detection (9 papers). The work is most often cited by research in Health Informatics (55 citations), Health Information Management (153 citations) and Artificial Intelligence (895 citations). Pedro Henriques Abreu has collaborated with scholars based in Portugal, Spain and Switzerland. Frequent co-authors include Miriam Seoane Santos, João Santos, J. Soares, Hélder Araújo, Pedro J. García-Laencina, Miguel Henriques Abreu, Daniel Castro Silva, Inês Domingues, Hugo Duarte and Tiago Cruz. Their work appears in journals such as Journal of Clinical Oncology, International Journal of Cancer and Expert Systems with 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.

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