Guilherme Aresta

2.6k citations
23 papers · 979 indexed · 1 hit paper · h-index 11
Topics
Retinal Imaging and Analysis (10 papers)Radiomics and Machine Learning in Medical Imaging (9 papers)AI in cancer detection (7 papers)
Partner nations
PortugalAustriaIran

In The Last Decade

Guilherme Aresta

20 papers receiving 943 citations

Hit Papers

Classification of breast cancer histology images using Co...20172026202020232017200400600

Peers

Guilherme Aresta
Comparison fields: 5 of 89
  • Radiology, Nuclear Medicine and Imaging 681
  • Artificial Intelligence 662
  • Computer Vision and Pattern Recognition 336
  • Ophthalmology 106
  • Neurology 93
Replace Teresa Araújo with:
Teresa Araújo Portugal
Adrián Colomer Spain
Huangjing Lin Hong Kong
Shekoofeh Azizi United States
Sebastian Otálora Switzerland
N. K. Timofeeva Netherlands
Iringo Kovacs Netherlands
Georgios C. Manikis Greece
Yanda Meng United Kingdom
Benoît Schmauch France
Guilherme Aresta relative to Teresa Araújo Portugal Teresa Araújo's profile →
Citations per field
00.5×1.5×
Teresa Araújo · 1×
Citations per year

Countries citing papers authored by Guilherme Aresta

Since Specialization
Citations

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

Fields of papers citing papers by Guilherme Aresta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guilherme Aresta

This figure shows the co-authorship network connecting the top 25 collaborators of Guilherme Aresta. A scholar is included among the top collaborators of Guilherme Aresta 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 Guilherme Aresta. Guilherme Aresta 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
1 2
2 0
3 2
4 4
5 9
6 25
7 5
8 19
9 1
10 95
11 43
12 0
13 22
14 25
15 4
16 24
17 2
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Classification of breast cancer histology images using Convolutional Neural Networksbreakdown →
648
19 16
20 14

About Guilherme Aresta

Guilherme Aresta is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Artificial Intelligence, having authored 23 papers that have together received 979 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers) and AI in cancer detection (7 papers). The work is most often cited by research in Health Informatics (43 citations), Radiology, Nuclear Medicine and Imaging (681 citations) and Artificial Intelligence (662 citations). Guilherme Aresta has collaborated with scholars based in Portugal, Austria and Iran. Frequent co-authors include Aurélio Campilho, Teresa Araújo, António Polónia, Catarina Eloy, Paulo Aguiar, José Rouco, Eduardo Castro, Ana Maria Mendonc̨a, Ângela Carneiro and Susana Penas. Their work appears in journals such as PLoS ONE, Scientific Reports 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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