Fábio Lopes

944 total citations
20 papers, 265 citations indexed

About

Fábio Lopes is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health and Artificial Intelligence. According to data from OpenAlex, Fábio Lopes has authored 20 papers receiving a total of 265 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 6 papers in Psychiatry and Mental health and 4 papers in Artificial Intelligence. Recurrent topics in Fábio Lopes's work include EEG and Brain-Computer Interfaces (12 papers), Epilepsy research and treatment (6 papers) and Neural dynamics and brain function (5 papers). Fábio Lopes is often cited by papers focused on EEG and Brain-Computer Interfaces (12 papers), Epilepsy research and treatment (6 papers) and Neural dynamics and brain function (5 papers). Fábio Lopes collaborates with scholars based in Portugal, Germany and Italy. Fábio Lopes's co-authors include César Teixeira, Mauro F. Pinto, António Dourado, Pedro Martins, Matthias Dümpelmann, Hugo Gonçalo Oliveira, Jorge Bernardino, Nuno Laranjeiro, Andreas Schulze‐Bonhage and Tiago Coelho and has published in prestigious journals such as Scientific Reports, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Fábio Lopes

19 papers receiving 258 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fábio Lopes Portugal 10 157 71 62 37 32 20 265
Nesma Houmani France 9 148 0.9× 37 0.5× 29 0.5× 27 0.7× 46 1.4× 21 283
Mauro F. Pinto Portugal 9 170 1.1× 76 1.1× 44 0.7× 36 1.0× 30 0.9× 17 265
Khansa Rasheed Pakistan 4 79 0.5× 32 0.5× 96 1.5× 15 0.4× 30 0.9× 4 287
Yogatheesan Varatharajah United States 10 240 1.5× 161 2.3× 35 0.6× 25 0.7× 24 0.8× 24 328
Iryna Korshunova Belgium 6 200 1.3× 104 1.5× 86 1.4× 21 0.6× 114 3.6× 7 553
Xinghua Yao China 10 73 0.5× 21 0.3× 52 0.8× 36 1.0× 31 1.0× 17 361
Susmita Saha Australia 7 173 1.1× 81 1.1× 34 0.5× 16 0.4× 41 1.3× 12 318
Patrick H. Luckett United States 11 86 0.5× 48 0.7× 40 0.6× 6 0.2× 36 1.1× 29 285
Dimitris Liparas Greece 7 78 0.5× 54 0.8× 51 0.8× 10 0.3× 22 0.7× 12 246

Countries citing papers authored by Fábio Lopes

Since Specialization
Citations

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

Fields of papers citing papers by Fábio Lopes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fábio Lopes

This figure shows the co-authorship network connecting the top 25 collaborators of Fábio Lopes. A scholar is included among the top collaborators of Fábio Lopes 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 Fábio Lopes. Fábio Lopes 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
1.
Lopes, Fábio, Mauro F. Pinto, António Dourado, et al.. (2024). Addressing data limitations in seizure prediction through transfer learning. Scientific Reports. 14(1). 14169–14169. 7 indexed citations
2.
Pinto, Mauro F., et al.. (2024). Concept-drifts adaptation for machine learning EEG epilepsy seizure prediction. Scientific Reports. 14(1). 8204–8204. 4 indexed citations
3.
Pinto, Mauro F., et al.. (2024). Classifier Combination Supported by the Sleep-Wake Cycle Improves EEG Seizure Prediction Performance. IEEE Transactions on Biomedical Engineering. 71(8). 2341–2351. 1 indexed citations
4.
Pinto, Mauro F., et al.. (2024). EEG epilepsy seizure prediction: the post-processing stage as a chronology. Scientific Reports. 14(1). 407–407. 8 indexed citations
5.
Pinto, Mauro F., Fábio Lopes, António Dourado, et al.. (2023). The goal of explaining black boxes in EEG seizure prediction is not to explain models' decisions. Epilepsia Open. 8(2). 285–297. 13 indexed citations
6.
Lopes, Fábio, Mauro F. Pinto, Francisco Sales, et al.. (2023). Unsupervised EEG preictal interval identification in patients with drug-resistant epilepsy. Scientific Reports. 13(1). 784–784. 9 indexed citations
7.
Lopes, Fábio, Mauro F. Pinto, António Dourado, et al.. (2023). Removing artefacts and periodically retraining improve performance of neural network-based seizure prediction models. Scientific Reports. 13(1). 5918–5918. 17 indexed citations
8.
Pinto, Mauro F., Tiago Coelho, Fábio Lopes, et al.. (2022). Interpretable EEG seizure prediction using a multiobjective evolutionary algorithm. Scientific Reports. 12(1). 4420–4420. 23 indexed citations
9.
Lopes, Fábio, et al.. (2022). EPIC: Annotated epileptic EEG independent components for artifact reduction. Scientific Data. 9(1). 512–512. 2 indexed citations
10.
Pinto, Mauro F., Fábio Lopes, Anna Maria Bianchi, et al.. (2021). Heart rate variability analysis for the identification of the preictal interval in patients with drug-resistant epilepsy. Scientific Reports. 11(1). 5987–5987. 21 indexed citations
11.
Pinto, Mauro F., et al.. (2021). A personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction. Scientific Reports. 11(1). 3415–3415. 43 indexed citations
12.
Lopes, Fábio, et al.. (2021). Automatic Electroencephalogram Artifact Removal Using Deep Convolutional Neural Networks. IEEE Access. 9. 149955–149970. 30 indexed citations
13.
Palmela, Carolina, et al.. (2020). Febrile Neutropenia in Patients with Solid Tumors Undergoing Intravenous Chemotherapy. Oncology Research and Treatment. 43(11). 605–612. 6 indexed citations
14.
Lopes, Fábio, César Teixeira, & Hugo Gonçalo Oliveira. (2020). Comparing Different Methods for Named Entity Recognition in Portuguese Neurology Text. Journal of Medical Systems. 44(4). 77–77. 14 indexed citations
15.
Passos‐Coelho, José Luís, et al.. (2020). Fatal Clostridium septicum febrile neutropenia during adjuvant chemotherapy for early breast cancer. BMJ Case Reports. 13(5). e233778–e233778.
16.
Casa-Nova, Mafalda, et al.. (2019). ONKOTEV Score as a Predictive Tool for Thromboembolic Events in Pancreatic Cancer—A Retrospective Analysis. The Oncologist. 25(2). e284–e290. 21 indexed citations
17.
18.
Lopes, Fábio, et al.. (2019). Automating orthogonal defect classification using machine learning algorithms. Future Generation Computer Systems. 102. 932–947. 28 indexed citations
19.
Lopes, Fábio, César Teixeira, & Hugo Gonçalo Oliveira. (2019). Contributions to Clinical Named Entity Recognition in Portuguese. 223–233. 10 indexed citations
20.
Velho, S., et al.. (2019). Comparison of body composition techniques in Portuguese patients with gastrointestinal cancer. Annals of Medicine. 51(sup1). 158–158. 1 indexed citations

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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