Listar GI-LIDIA - Artigos por título
Mostrando ítems 1-20 de 48
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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 ... -
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 ... -
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 ... -
A One-Class Classification method based on Expanded Non-Convex Hulls
(Elsevier, 2023)[Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ... -
A scalable decision-tree-based method to explain interactions in dyadic data
(Elsevier, 2019-12)[Abstract]: Gaining relevant insight from a dyadic dataset, which describes interactions between two entities, is an open problem that has sparked the interest of researchers and industry data scientists alike. However, ... -
A scalable saliency-based feature selection method with instance-level information
(Elsevier, 2019-11)[Abstract]: Classic feature selection techniques remove irrelevant or redundant features to achieve a subset of relevant features in compact models that are easier to interpret and so improve knowledge extraction. Most ... -
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 ... -
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 ... -
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 ... -
Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach
(Springer Nature, 2023-11)[Abstract]: Any machine learning (ML) model is highly dependent on the data it uses for learning, and this is even more important in the case of deep learning models. The problem is a data bottleneck, i.e. the difficulty ... -
Anomaly Detection on Natural Language Processing to Improve Predictions on Tourist Preferences
(MDPI, 2022)[Abstract] Argumentation-based dialogue models have shown to be appropriate for decision contexts in which it is intended to overcome the lack of interaction between decision-makers, either because they are dispersed, they ... -
Artificial Intelligence in Pre-University Education: What and How to Teach
(MDPI, 2020-08-26)[Abstract] The present paper is part of the European Erasmus+ project on educational innovation led by the UDC and entitled “AI+: Developing an Artificial Intelligence Curriculum adapted to European High School”. In this ... -
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 ... -
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 ... -
Community detection and social network analysis based on the Italian wars of the 15th century
(Elsevier, 2020)[Abstract]: In this contribution we study social network modelling by using human interaction as a basis. To do so, we propose a new set of functions, affinities, designed to capture the nature of the local interactions ... -
Computer-assisted analysis of polysomnographic recordings improves interscorer associated agreement and scoring times
(Public Library of Science, 2022-09)[Abstract]: Study objectives To investigate inter-scorer agreement and scoring time differences associated with visual and computer-assisted analysis of polysomnographic (PSG) recordings. Methods A group of 12 expert scorers ... -
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 ... -
Data-driven predictive maintenance framework for railway systems
(IOS Press, 2023)[Abstract]: The emergence of the Industry 4.0 trend brings automation and data exchange to industrial manufacturing. Using computational systems and IoT devices allows businesses to collect and deal with vast volumes of ... -
Dealing with heterogeneity in the context of distributed feature selection for classification
(Springer, 2021)[Abstract]: Advances in the information technologies have greatly contributed to the advent of larger datasets. These datasets often come from distributed sites, but even so, their large size usually means they cannot be ... -
Distributed classification based on distances between probability distributions in feature space
(Elsevier, 2019-09)[Abstract]: We consider a distributed framework where training and test samples drawn from the same distribution are available, with the training instances spread across disjoint nodes. In this setting, a novel learning ...
