Author

Marta Molinas

Norwegian University of Science and TechnologyORCID 0000-0002-8791-0917Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Assay:electronic health records· 3 Research Focus:benchmarking· 2 Research Focus:dimensionality reduction· 2 Approach:statistical model· 2 Research Focus:clustering· 1 Approach:machine learning (classical)· 1 Approach:optimal transport· 1

Frequent Co-Authors

Andrés Felipe SoleriD· 3 shared Eduardo GiraldoiD· 2 shared Håkon Stenwig· 1 shared Junya Furuki· 1 shared Luis Alfredo MoctezumaiD· 1 shared Maximiliano Bueno-LópeziD· 1 shared Pablo A. Muñoz-GutiérreziD· 1 shared Takashi AbeiD· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 18 mutual co-author links

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3 shared papersNeuroscience

Andrés Felipe SolerORCID

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3 papers

Recent·Most cited

NeuroscienceInternational Conference on Machine Learning and ApplicationsPeer-reviewedDec 1, 2022

Automatic Sleep Stage Classification with Optimized Selection of EEG Channels

Håkon Stenwig, Andrés Felipe Soler, Junya Furuki…·Marta Molinas

This paper presents an ensemble algorithm that automatically classifies sleep stages using an optimized minimal number of EEG channels, achieving high accuracy with only 3 channels.

7 citations

electronic health recordsmachine learning (classical)

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NeuroscienceScientific ReportsPeer-reviewedJul 2, 2022

Automated methodology for optimal selection of the minimum electrode subset for accurate EEG source estimation based on Genetic Algorithm optimization

Andrés Felipe Soler, Luis Alfredo Moctezuma, Eduardo Giraldo, Marta Molinas

This paper optimizes EEG electrode selection using a genetic algorithm to maintain high localization accuracy with fewer electrodes.

26 citations

electronic health recordsoptimal transport

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NeuroscienceFrontiers in NeurosciencePeer-reviewedFeb 28, 2020

Low-Density EEG for Neural Activity Reconstruction Using Multivariate Empirical Mode Decomposition

Andrés Felipe Soler, Pablo A. Muñoz-Gutiérrez, Maximiliano Bueno-López…·Marta Molinas

This paper improves neural activity reconstruction from low-density EEG using Multivariate Empirical Mode Decomposition (MEMD) and shows significant error reduction in both real and simulated data.

34 citations

electronic health recordsstatistical model

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