Iván Olier
Orcid: 0000-0002-5679-7501
According to our database1,
Iván Olier
authored at least 36 papers
between 2005 and 2024.
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Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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On csauthors.net:
Bibliography
2024
Predicting Decompensation Risk in Intensive Care Unit Patients Using Machine Learning.
Algorithms, 2024
2023
2022
Proceedings of the International Joint Conference on Neural Networks, 2022
2021
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021
2020
Proceedings of the ECML PKDD 2020 Workshops, 2020
Explaining the Neural Network: A Case Study to Model the Incidence of Cervical Cancer.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020
2019
Multi-task learning with a natural metric for quantitative structure activity relationship learning.
J. Cheminformatics, 2019
Classifying and Grouping Mammography Images into Communities Using Fisher Information Networks to Assist the Diagnosis of Breast Cancer.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019
A Voting Ensemble Method to Assist the Diagnosis of Prostate Cancer Using Multiparametric MRI.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019
Proceedings of the International Joint Conference on Neural Networks, 2019
Comparative Analysis for Computer-Based Decision Support: Case Study of Knee Osteoarthritis.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019
A Comparative Assessment of Feed-Forward and Convolutional Neural Networks for the Classification of Prostate Lesions.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019
2018
Mach. Learn., 2018
2015
From raw data to data-analysis for magnetic resonance spectroscopy - the missing link: jMRUI2XML.
BMC Bioinform., 2015
Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (ECMLPKDD 2015), 2015
2014
Probability Ridges and Distortion Flows: Visualizing Multivariate Time Series Using a Variational Bayesian Manifold Learning Method.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014
Semi-supervised source extraction methodology for the nosological imaging of glioblastoma response to therapy.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014
2013
2011
A variational Bayesian approach for the robust analysis of the cortical silent period from EMG recordings of brain stroke patients.
Neurocomputing, 2011
A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011
Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2011
2010
The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain masses.
BMC Bioinform., 2010
SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system.
BMC Bioinform., 2010
Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010
Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010
2008
Neural Networks, 2008
J. Math. Model. Algorithms, 2008
Proceedings of the International Joint Conference on Neural Networks, 2008
Proceedings of the International Joint Conference on Neural Networks, 2008
2007
Proceedings of the Intelligent Data Engineering and Automated Learning, 2007
2006
Time Series Relevance Determination Through a Topology-Constrained Hidden Markov Model.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2006
2005
Comparative Assessment of the Robustness of Missing Data Imputation Through Generative Topographic Mapping.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005