Listar GI-LIDIA - Artigos por data de publicación
Mostrando ítems 1-20 de 64
-
Improving detection of apneic events by learning from examples and treatment of missing data
(I O S Press, 2014)[Abstract] This paper presents a comparative study over the respiratory pattern classification task involving three missing data imputation techniques, and four different machine learning algorithms. The main goal was to ... -
A Taxonomy-Based Usability Study of an Intelligent Speed Adaptation Device
(Taylor & Francis Inc., 2014-04-04)[Abstract] Usability studies are often based on ad hoc definitions of usability. These studies can be difficult to generalize, they might have a steep learning curve, and there is always the danger of being inconsistent ... -
Intelligent approach for analysis of respiratory signals and oxygen saturation in the sleep apnea/hypopnea syndrome
(Bentham Open, 2014-06-13)This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in ... -
Computer-Assisted Diagnosis of the Sleep Apnea-Hypopnea Syndrome: A Review
(Hindawi Publishing Corporation, 2015)Automatic diagnosis of the Sleep Apnea-Hypopnea Syndrome (SAHS) has become an important area of research due to the growing interest in the field of sleep medicine and the costs associated with its manual diagnosis. The ... -
Commentaries on Viewpoint: The ongoing need for good physiological investigation: Obstructive sleep apnea in HIV patients as a paradigm
(American Physiological Society, 2015-01-15)[Abstract] The intriguing paradigm put forth by Darquenne et al. (3) highlighted that improved therapy against human immunodeficiency virus (HIV) has come at the cost of elevated rates of chronic diseases, such as obstructive ... -
Automatic classification of respiratory patterns involving missing data imputation techniques
(Academic Press, 2015-10)[Abstract] A comparative study of the respiratory pattern classification task, involving five missing data imputation techniques and several machine learning algorithms is presented in this paper. The main goal was to ... -
A comparison of performance of K-complex classification methods using feature selection
(2016-01-20)[Abstract] The main objective of this work is to obtain a method that achieves the best accuracy results with a low false positive rate in the classification of K-complexes, a kind of transient waveform found in the ... -
Spectral Heart Rate Variability analysis using the heart timing signal for the screening of the Sleep Apnea–Hypopnea Syndrome
(Pergamon Press, 2016-04-01)[Abstract] Some approaches have been published in the past using Heart Rate Variability (HRV) spectral features for the screening of Sleep Apnea–Hypopnea Syndrome (SAHS) patients. However there is a big variability among ... -
A knowledge model for the development of a framework for hypnogram construction
(Elsevier BV, 2017-02-15)[Abstract] We describe a proposal of a knowledge model for the development of a framework for hypnogram construction from intelligent analysis of pulmonology and electrophysiological signals. Throughout the twentieth ... -
On the scalability of feature selection methods on high-dimensional data
(Springer, 2018)[Abstract]: Lately, derived from the explosion of high dimensionality, researchers in machine learning became interested not only in accuracy, but also in scalability. Although scalability of learning methods is a trending ... -
Emerging technologies in artificial intelligence: quantum rule-based systems
(Springer, 2018)[Abstract]: This article tries to establish synergies between two areas of research and development that are apparently disconnected: artificial intelligence (AI) and quantum computing (QC). The article begins with a brief ... -
A Systematic and Generalizable Approach to the Heuristic Evaluation of User Interfaces
(Taylor & Francis, 2018-01-24)[Abstract]: Heuristic evaluation is one of the most actively used techniques for analyzing usability, as it is quick and inexpensive. This technique is based on following a given set of heuristics, which are typically ... -
Revisiting the Wang–Mendel algorithm for fuzzy classification
(John Wiley & Sons Ltd, 2018-02-06)[Abstract]: In this paper, we review the Wang–Mendel algorithm for the induction of fuzzy IF-THEN rules in the context of classification problems. A general fuzzy inference architecture for classification is proposed with ... -
A systematic approach to API usability: Taxonomy-derived criteria and a case study
(Elsevier B.V., 2018-05)[Abstract]: CONTEXT. The currently existing literature about Application Program Interface (API) usability is heterogeneous in terms of goals, scope, and audience; and its connection to accepted definitions of usability ... -
Insights into distributed feature ranking
(Elsevier, 2019)[Abstract]: In an era in which the volume and complexity of datasets is continuously growing, feature selection techniques have become indispensable to extract useful information from huge amounts of data. However, existing ... -
Ensembles for feature selection: A review and future trends
(Elsevier, 2019)[Abstract]: Ensemble learning is a prolific field in Machine Learning since it is based on the assumption that combining the output of multiple models is better than using a single model, and it usually provides good ... -
Large scale anomaly detection in mixed numerical and categorical input spaces
(Elsevier, 2019)[Abstract]: This work presents the ADMNC method, designed to tackle anomaly detection for large-scale problems with a mixture of categorical and numerical input variables. A flexible parametric probability measure is ... -
On developing an automatic threshold applied to feature selection ensembles
(Elsevier, 2019-01)[Abstract]: Feature selection ensemble methods are a recent approach aiming at adding diversity in sets of selected features, improving performance and obtaining more robust and stable results. However, using an ensemble ... -
A Convolutional Network for Sleep Stages Classification
(2019-02)[Abstract]: Sleep stages classification is a crucial task in the context of sleep studies. It involves the simultaneous analysis of multiple signals recorded during sleep. However, it is complex and tedious, and even the ... -
Data analysis and feature selection for predictive maintenance: A case-study in the metallurgic industry
(Elsevier Ltd, 2019-06)[Abstract]: Proactive Maintenance practices are becoming more standard in industrial environments, with a direct and profound impact on the competitivity within the sector. These practices demand the continuous monitorization ...
