Margarida Silveira

1.7k total citations
58 papers, 1.2k citations indexed

About

Margarida Silveira is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Psychiatry and Mental health. According to data from OpenAlex, Margarida Silveira has authored 58 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 7 papers in Psychiatry and Mental health. Recurrent topics in Margarida Silveira's work include Medical Image Segmentation Techniques (16 papers), Image Retrieval and Classification Techniques (9 papers) and Dementia and Cognitive Impairment Research (7 papers). Margarida Silveira is often cited by papers focused on Medical Image Segmentation Techniques (16 papers), Image Retrieval and Classification Techniques (9 papers) and Dementia and Cognitive Impairment Research (7 papers). Margarida Silveira collaborates with scholars based in Portugal, United States and Spain. Margarida Silveira's co-authors include Jorge S. Marques, Sandra Heleno, Jacinto C. Nascimento, Carlos Cabral, A. Marçal, Teresa Mendonça, Jorge Rozeira, Junji Maeda, Pedro Morgado and Durval C. Costa and has published in prestigious journals such as PLoS ONE, Scientific Reports and Arteriosclerosis Thrombosis and Vascular Biology.

In The Last Decade

Margarida Silveira

53 papers receiving 1.2k citations

Peers

Margarida Silveira
Comparison fields: 5 of 132
  • Artificial Intelligence 424
  • Oncology 319
  • Computer Vision and Pattern Recognition 266
  • Biomedical Engineering 152
  • Radiology, Nuclear Medicine and Imaging 135
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Citations per field, relative to Margarida Silveira
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Citations per year, relative to Margarida Silveira
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Countries citing papers authored by Margarida Silveira

Since Specialization
Citations

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

Fields of papers citing papers by Margarida Silveira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Margarida Silveira. 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 Margarida Silveira. The network helps show where Margarida Silveira may publish in the future.

Co-authorship network of co-authors of Margarida Silveira

This figure shows the co-authorship network connecting the top 25 collaborators of Margarida Silveira. A scholar is included among the top collaborators of Margarida Silveira 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 Margarida Silveira. Margarida Silveira 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
# Work Indexed citations
1 0
2 3
3 30
4 4
5 5
6 8
7
Detection of human ovarian carcinoma from blood samples using scent dogs
0
8 41
9 59
10 79
11 10
12 12
13 8
14 7
15 1
16 7
17 16
18 32
19 37
20 16

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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