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ORCIDMariana Recamonde Mendoza
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2020 – today
- 2024
[j10]Kayuã Oleques Paim
, Ricardo Rohweder, Mariana Recamonde Mendoza, Rodrigo Brandão Mansilha, Weverton Cordeiro:
Acoustic identification of Ae. aegypti mosquitoes using smartphone apps and residual convolutional neural networks. Biomed. Signal Process. Control. 95: 106342 (2024)- [j9]Heloísa Oss Boll, Ali Amirahmadi, Mirfarid Musavian Ghazani, Wagner Ourique de Morais, Edison Pignaton de Freitas, Amira Soliman, Farzaneh Etminani, Stefan Byttner, Mariana Recamonde Mendoza:
Graph neural networks for clinical risk prediction based on electronic health records: A survey. J. Biomed. Informatics 151: 104616 (2024) - [c16]Renan Soares de Andrades, Mariana Recamonde Mendoza:
Predicting Cancer Driver Genes: Leveraging Graph Convolutional Networks and Ensemble Learning. CIBCB 2024: 1-8 - [i9]Heloísa Oss Boll, Ali Amirahmadi, Amira Soliman, Stefan Byttner, Mariana Recamonde Mendoza:
Graph Neural Networks for Heart Failure Prediction on an EHR-Based Patient Similarity Graph. CoRR abs/2411.19742 (2024) - 2023
- [c15]Emanoel Aurelio Vianna Fabiano, Mariana Recamonde Mendoza:
Prediction of Cancer-Related miRNA Targets Using an Integrative Heterogeneous Graph Neural Network-Based Method. BRACIS (3) 2023: 346-360 - [c14]Daniel M. Kuhn, Melina Loreto, Mariana Recamonde Mendoza, João Luiz Dihl Comba, Viviane Pereira Moreira:
Explainability of COVID-19 Classification Models Using Dimensionality Reduction of SHAP Values. BRACIS (1) 2023: 415-430 - [p1]Ana L. C. Bazzan, Anderson R. Tavares, André G. Pereira, Cláudio R. Jung, Jacob Scharcanski, Joel Luís Carbonera, Luís C. Lamb, Mariana Recamonde Mendoza, Thiago L. T. da Silveira, Viviane P. Moreira:
"A Nova Eletricidade": Aplicações, Riscos e Tendências da IA Moderna. Escola de Computação PPGC/UFRGS 50 Anos 2023: 167-209 - [i8]Kayuã Oleques Paim, Ricardo Rohweder, Mariana Recamonde Mendoza, Rodrigo Brandão Mansilha, Weverton Cordeiro:
Acoustic Identification of Ae. aegypti Mosquitoes using Smartphone Apps and Residual Convolutional Neural Networks. CoRR abs/2306.10091 (2023) - [i7]Noemí Maritza Lapa Romero, Ricco Vasconcellos, Mariana Recamonde Mendoza, João Luiz Dihl Comba:
COVID-VR: A Deep Learning COVID-19 Classification Model Using Volume-Rendered Computer Tomography. CoRR abs/2308.01433 (2023) - [i6]Ana L. C. Bazzan, Anderson R. Tavares, André G. Pereira, Cláudio R. Jung, Jacob Scharcanski, Joel Luis Carbonera, Luís C. Lamb, Mariana Recamonde Mendoza, Thiago L. T. da Silveira, Viviane P. Moreira:
"A Nova Eletricidade: Aplicações, Riscos e Tendências da IA Moderna - "The New Electricity": Applications, Risks, and Trends in Current AI. CoRR abs/2310.18324 (2023) - 2022
- [j8]Renan Andrades, Mariana Recamonde Mendoza:
Machine learning methods for prediction of cancer driver genes: a survey paper. Briefings Bioinform. 23(3) (2022) - [j7]Felipe Colombelli, Thayne Woycinck Kowalski, Mariana Recamonde Mendoza:
A hybrid ensemble feature selection design for candidate biomarkers discovery from transcriptome profiles. Knowl. Based Syst. 254: 109655 (2022) - [j6]João Schapke, Anderson R. Tavares, Mariana Recamonde Mendoza:
EPGAT: Gene Essentiality Prediction With Graph Attention Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1615-1626 (2022) - [c13]Thomas V. Fontanari, Tiago Comassetto Fróes, Mariana Recamonde Mendoza:
Cross-validation Strategies for Balanced and Imbalanced Datasets. BRACIS (1) 2022: 626-640 - [c12]Carlos Daniel Andrade, Thomas V. Fontanari, Mariana Recamonde Mendoza:
Study on the Complexity of Omics Data: An Analysis for Cancer Survival Prediction. BSB 2022: 44-55 - 2021
- [j5]Marcelo Schreiber Fernandes, Weverton Cordeiro, Mariana Recamonde Mendoza:
Detecting Aedes aegypti mosquitoes through audio classification with convolutional neural networks. Comput. Biol. Medicine 129: 104152 (2021) - [j4]Grasiela Marcon, Flávia de Ávila Pereira, Aline Zimerman, Bruno Castro da Silva, Lisia von Diemen, Ives Cavalcante Passos, Mariana Recamonde Mendoza:
Patterns of high-risk drinking among medical students: A web-based survey with machine learning. Comput. Biol. Medicine 136: 104747 (2021) - [c11]Bernardo Trevizan, Mariana Recamonde Mendoza:
Ensemble Feature Selection Compares to Meta-analysis for Breast Cancer Biomarker Identification from Microarray Data. ICCSA (1) 2021: 162-178 - [i5]Felipe Colombelli, Thayne Woycinck Kowalski, Mariana Recamonde Mendoza:
A Hybrid Ensemble Feature Selection Design for Candidate Biomarkers Discovery from Transcriptome Profiles. CoRR abs/2108.00290 (2021) - [i4]Renan Andrades, Mariana Recamonde Mendoza:
Machine learning methods for prediction of cancer driver genes: a survey paper. CoRR abs/2109.13685 (2021) - 2020
- [j3]Bernardo Trevizan, Jorge C. Chamby-Diaz, Ana L. C. Bazzan, Mariana Recamonde Mendoza:
A comparative evaluation of aggregation methods for machine learning over vertically partitioned data. Expert Syst. Appl. 152: 113406 (2020) - [j2]Soheil Feizi, Gerald T. Quon, Mariana Recamonde Mendoza, Muriel Médard, Manolis Kellis, Ali Jadbabaie:
Spectral Alignment of Graphs. IEEE Trans. Netw. Sci. Eng. 7(3): 1182-1197 (2020) - [c10]Hortênsia Costa Barcelos, Mariana Recamonde Mendoza, Viviane Pereira Moreira:
Identifying and Fusing Duplicate Features for Data Mining. SBBD 2020: 133-144 - [i3]João Schapke, Anderson R. Tavares, Mariana Recamonde Mendoza:
EPGAT: Gene Essentiality Prediction With Graph Attention Networks. CoRR abs/2007.09671 (2020) - [i2]Marcelo Schreiber Fernandes, Weverton Cordeiro, Mariana Recamonde Mendoza:
Detecting Aedes Aegypti Mosquitoes through Audio Classification with Convolutional Neural Networks. CoRR abs/2008.09024 (2020)
2010 – 2019
- 2019
- [c9]Jorge Cristhian Chamby-Diaz, Mariana Recamonde Mendoza, Ana Lúcia C. Bazzan:
Dynamic Correlation-Based Feature Selection for Feature Drifts in Data Streams. BRACIS 2019: 198-203 - 2018
- [c8]Jorge C. Chamby-Diaz, Mariana Recamonde Mendoza, Ana L. C. Bazzan, Ricardo Grunitzki:
Adaptive Incremental Gaussian Mixture Network for Non-Stationary Data Stream Classification. IJCNN 2018: 1-8 - 2017
- [c7]Matheus Alves, Ana L. C. Bazzan, Mariana Recamonde Mendoza:
Social-Training: Ensemble Learning with Voting Aggregation for Semi-supervised Classification Tasks. BRACIS 2017: 7-12 - 2016
- [j1]Mariana Recamonde Mendoza, Ana L. C. Bazzan:
Social choice in distributed classification tasks: Dealing with vertically partitioned data. Inf. Sci. 332: 56-71 (2016) - [i1]Soheil Feizi, Gerald T. Quon, Mariana Recamonde Mendoza, Muriel Médard, Manolis Kellis, Ali Jadbabaie:
Spectral Alignment of Networks. CoRR abs/1602.04181 (2016) - 2013
- [c6]Mariana Recamonde Mendoza, Ana Lúcia C. Bazzan:
The Wisdom of Crowds in Bioinformatics: What Can We Learn (and Gain) from Ensemble Predictions? AAAI 2013 - 2012
- [c5]Mariana Recamonde Mendoza, Fabrício Martins Lopes, Ana Lúcia C. Bazzan:
Reverse engineering of GRNs: an evolutionary approach based on the tsallis entropy. GECCO 2012: 185-192 - [c4]Mariana Recamonde Mendoza, Ana L. C. Bazzan:
On the Ensemble Prediction of Gene Regulatory Networks: A Comparative Study. SBRN 2012: 55-60 - [c3]Mariana Recamonde Mendoza, Adriano Velasque Werhli, Ana L. C. Bazzan:
An Epsilon-Greedy Mutation Operator Based on Prior Knowledge for GA Convergence and Accuracy Improvement: An Application to Networks Inference. SBRN 2012: 67-72 - [c2]Mariana Recamonde Mendoza, Guilherme C. da Fonseca, Guilherme L. de Morais, Ronnie Alves, Ana L. C. Bazzan, Rogerio Margis:
RFMirTarget: A Random Forest Classifier for Human miRNA Target Gene Prediction. BSB 2012: 97-108 - 2011
- [c1]Mariana Recamonde Mendoza, Ana Lúcia C. Bazzan:
Evolving random boolean networks with genetic algorithms for regulatory networks reconstruction. GECCO 2011: 291-298
Coauthor Index
aka: Ana Lúcia C. Bazzan
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