Eduardo Luz

2.5k total citations · 1 hit paper
44 papers, 1.6k citations indexed

About

Eduardo Luz is a scholar working on Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Signal Processing. According to data from OpenAlex, Eduardo Luz has authored 44 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cardiology and Cardiovascular Medicine, 13 papers in Cognitive Neuroscience and 13 papers in Signal Processing. Recurrent topics in Eduardo Luz's work include ECG Monitoring and Analysis (14 papers), EEG and Brain-Computer Interfaces (13 papers) and Biometric Identification and Security (7 papers). Eduardo Luz is often cited by papers focused on ECG Monitoring and Analysis (14 papers), EEG and Brain-Computer Interfaces (13 papers) and Biometric Identification and Security (7 papers). Eduardo Luz collaborates with scholars based in Brazil, United States and United Kingdom. Eduardo Luz's co-authors include David Menotti, William Robson Schwartz, Guillermo Cámara-Chávez, Gladston Moreira, Pedro Silva, Victor Hugo C. de Albuquerque, João Paulo Papa, Thiago Nunes, Guilherme Silva and Rodrigo Silva and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Applied Energy.

In The Last Decade

Eduardo Luz

37 papers receiving 1.6k citations

Hit Papers

ECG-based heartbeat classification for arrhythmia detecti... 2015 2026 2018 2022 2015 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. ECG-based heartbeat classification for arrhythmia detection: A survey
    2015 626 citations Eduardo Luz, William Robson Schwartz et al. Computer Methods and Programs in Biomedicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eduardo Luz Brazil 17 1.0k 813 426 277 224 44 1.6k
Feifei Liu China 16 1.1k 1.0× 654 0.8× 376 0.9× 190 0.7× 244 1.1× 48 1.5k
Ali Ghaffari Iran 17 614 0.6× 418 0.5× 320 0.8× 97 0.4× 177 0.8× 81 1.1k
Firdaus Firdaus Indonesia 18 437 0.4× 264 0.3× 143 0.3× 199 0.7× 124 0.6× 123 1.0k
Semih Ergi̇n Türkiye 12 376 0.4× 245 0.3× 226 0.5× 212 0.8× 85 0.4× 45 808
Arvind Kumar Tiwari India 12 298 0.3× 177 0.2× 157 0.4× 181 0.7× 70 0.3× 67 929
Bambang Tutuko Indonesia 15 339 0.3× 199 0.2× 123 0.3× 119 0.4× 93 0.4× 84 769
Sung Bum Pan South Korea 15 244 0.2× 216 0.3× 222 0.5× 131 0.5× 30 0.1× 94 875
Mehrsan Javan Canada 14 251 0.2× 170 0.2× 178 0.4× 375 1.4× 49 0.2× 26 1.1k
Satria Mandala Indonesia 17 232 0.2× 92 0.1× 84 0.2× 190 0.7× 69 0.3× 95 802
Enrique Muñoz Italy 15 202 0.2× 190 0.2× 147 0.3× 113 0.4× 17 0.1× 42 849

Countries citing papers authored by Eduardo Luz

Since Specialization
Citations

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

Fields of papers citing papers by Eduardo Luz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eduardo Luz

This figure shows the co-authorship network connecting the top 25 collaborators of Eduardo Luz. A scholar is included among the top collaborators of Eduardo Luz 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 Eduardo Luz. Eduardo Luz 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.
2.
Silva, Guilherme, et al.. (2024). Periocular EfficientNet: A Deep Model for Periocular Recognition. 1–6.
3.
Luz, Eduardo, et al.. (2024). Towards robust ferrous scrap material classification with deep learning and conformal prediction. Engineering Applications of Artificial Intelligence. 140. 109724–109724. 5 indexed citations
4.
Luz, Eduardo, et al.. (2023). Using Mobile Edge AI to Detect and Map Diseases in Citrus Orchards. Sensors. 23(4). 2165–2165. 18 indexed citations
5.
Silva, Pedro, et al.. (2023). How Good Is ChatGPT For Detecting Hate Speech In Portuguese?. 94–103. 6 indexed citations
6.
7.
Rezende, Mariana T., Andrea Bianchi, Cláudia Martins Carneiro, et al.. (2022). A Cytopathologist Eye Assistant for Cell Screening. SHILAP Revista de lepidopterología. 2(4). 659–674.
8.
Moreira, Gladston, et al.. (2022). A Decidability-Based Loss Function. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8.
9.
Rezende, Mariana T., Andrea Bianchi, Cláudia Martins Carneiro, et al.. (2021). A Deep Learning Ensemble Method to Assist Cytopathologists in Pap Test Image Classification. Journal of Imaging. 7(7). 111–111. 38 indexed citations
10.
Luz, Eduardo, et al.. (2021). Dataset for Hop varieties classification. SHILAP Revista de lepidopterología. 38. 107312–107312. 2 indexed citations
11.
Cabral, Thales Wulfert, et al.. (2021). Arrhythmia classification from single-lead ECG signals using the inter-patient paradigm. Computer Methods and Programs in Biomedicine. 202. 105948–105948. 65 indexed citations
12.
Luz, Eduardo, Pedro Silva, Rodrigo Silva, & Gladston Moreira. (2020). Towards an Efficient Deep Learning Model for COVID-19 Patterns Detection in X-ray Images. arXiv (Cornell University). 16 indexed citations
13.
Silva, Pedro, Eduardo Luz, Guilherme Silva, et al.. (2020). COVID-19 detection in CT images with deep learning: A voting-based scheme and cross-datasets analysis. Informatics in Medicine Unlocked. 20. 100427–100427. 171 indexed citations
14.
Silva, Pedro, Eduardo Luz, Guilherme Silva, et al.. (2020). Towards better heartbeat segmentation with deep learning classification. Scientific Reports. 10(1). 20701–20701. 25 indexed citations
15.
Moreira, Gladston, et al.. (2019). Spatial cluster analysis using particle swarm optimization and dispersion function. Communications in Statistics - Simulation and Computation. 50(8). 2368–2385. 3 indexed citations
16.
García, Gabriel, Gladston Moreira, David Menotti, & Eduardo Luz. (2017). Inter-Patient ECG Heartbeat Classification with Temporal VCG Optimized by PSO. Scientific Reports. 7(1). 10543–10543. 94 indexed citations
17.
Moreira, Gladston, Eduardo Luz, & David Menotti. (2016). Optimizing acceptance frontier using PSO and GA for multiple signature iris recognition. 4. 4592–4598. 1 indexed citations
18.
Luz, Eduardo, William Robson Schwartz, Guillermo Cámara-Chávez, & David Menotti. (2015). ECG-based heartbeat classification for arrhythmia detection: A survey. Computer Methods and Programs in Biomedicine. 127. 144–164. 626 indexed citations breakdown →
19.
Luz, Eduardo, et al.. (2015). Automatic cardiac arrhythmia detection and classification using vectorcardiograms and complex networks. PubMed. 2015. 5203–5206. 8 indexed citations
20.
Luz, Eduardo & David Menotti. (2011). How the choice of samples for building arrhythmia classifiers impact their performances. PubMed. 2011. 4988–4991. 21 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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