Inês Dutra

797 citations
86 papers · 574 · h-index 14

Impact in

Papers in

Inês Dutra

74 papers receiving 543 citations

Peers

Inês Dutra
Comparison fields: 5 of 89
  • Hardware and Architecture 93
  • Artificial Intelligence 278
  • Computer Networks and Communications 161
  • Information Systems 153
  • Health Informatics 8
Replace Christos Kloukinas with:
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Matthew Simpson United States
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Noël De Palma France
Ivor Spence United Kingdom
Myungho Lee South Korea
L Zheng United States
Zhan Shi China
Saeed Iqbal Pakistan
Yongwang Zhao China
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Citations per field
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Citations per year

Countries citing papers authored by Inês Dutra

Since Specialization
Citations

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

Fields of papers citing papers by Inês Dutra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Inês Dutra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Inês Dutra Line = papers co-authored together Inês Dutra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201461
2 200542
3
View learning for statistical relational learning: with an application to mammography
200538
4 202228
5 202027
6
Knowledge discovery from structured mammography reports using inductive logic programming.
200523
7 201120
8
Performance of the compiler-based Andorra-I system
199319
9 200319
10 200517
11 201615
12 201415
13 202014
14
Establishing Identity Equivalence in Multi-Relational Domains
200513
15 201211
16
Strategies for scheduling and- and or- work in parallel logic programming systems
199410
17
Leveraging Expert Knowledge to Improve Machine-Learned Decision Support Systems.
201510
18 20159
19 20238
20 20038

About Inês Dutra

Inês Dutra is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Hardware and Architecture and Molecular Biology, having authored 86 papers that have together received 574 indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (18 papers), Parallel Computing and Optimization Techniques (17 papers), Cloud Computing and Resource Management (15 papers), Biomedical Text Mining and Ontologies (11 papers), AI in cancer detection (9 papers), Data Mining Algorithms and Applications (9 papers), Distributed systems and fault tolerance (7 papers) and Bayesian Modeling and Causal Inference (7 papers). The work is most often cited by research in Hardware and Architecture (93 citations), Artificial Intelligence (278 citations), Computer Networks and Communications (161 citations), Information Systems (153 citations) and Health Informatics (8 citations). Inês Dutra has collaborated with scholars based in Portugal, Brazil and United States. Frequent co-authors include Vı́tor Santos Costa, Elizabeth S. Burnside, David Page, Jesse Davis, Fernando Silva, Jude Shavlik, Paulino Sousa, Pedro Ferreira, David Page and Raghu Ramakrishnan. Their work appears in journals such as International Journal of Immunogenetics, Lecture notes in computer science, Software Practice and Experience, Sensors and Journal of Parallel and Distributed Computing.

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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