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Análisis del nivel de atención de los alumnos en clase utilizando NeuroSky’s MindWave Mobile
(UCOPress, 2018)
Este artículo describe un software en Android específico para el dispositivo NeuroSky’s MindWave Mobile, con el que poder medir el nivel de atención de los estudiantes de grado en informática durante las sesiones tradicionales ...
Memetic Evolutionary Multi-Objective Neural Network Classifier to Predict Graft Survival in Liver Transplant Patients
(2017-02-17)
In liver transplantation, matching donor and recipient is a
problem that can be solved using machine learning techniques.
In this paper we consider a liver transplant dataset
obtained from eleven Spanish hospitals, ...
Graph-Based Feature Selection Approach for Molecular Activity Prediction
(American Chemical Society, 2022)
In the construction of QSAR models for the prediction of molecular
activity, feature selection is a common task aimed at improving the results and
understanding of the problem. The selection of features allows elimination ...
Effective Feature Selection Method for Class-Imbalance Datasets Applied to Chemical Toxicity Prediction
(American Chemical Society, 2021)
During the drug development process, it is common to carry out toxicity tests and adverse effect studies, which are essential to guarantee patient safety and the success of the research. The use of in silico quantitative ...
Cooperative coevolutionary instance selection for multilabel problems
(Elsevier, 2021)
Multilabel classification as a data mining task has recently attracted greater research interest. Many
current data mining applications address problems having instances that belong to more than one
class, which requires ...
Reducing gaps in quantitative association rules: A genetic programming free-parameter algorithm
(IOS Press, 2014)
The extraction of useful information for decision making is a challenge in many different domains. Association rule mining is one of the most important techniques in this field, discovering relationships of interest among ...
Democratization of advanced models for data science
(Universidad de Córdoba, UCOPress, 2024)
En las últimas décadas, la mayoría de las empresas y organizaciones han generado y almacenado enormes cantidades de datos procedentes de diversas fuentes como transacciones financieras, interacciones con clientes, registros ...
Recomputing Causality Assignments on Lumped Process Models When Adding New Simplification Assumptions
(MDPI, 2018)
This paper presents a new algorithm for the resolution of over-constrained lumped process
systems, where partial differential equations of a continuous time and space model of the system
are reduced into ordinary ...
Effects of hypopressiveexercises on post-partum abdominal diastasis, trunk circumference and mechanical properties of abdominopelvic tissues: a case series
(Taylor & Francis, 2023)
Background: Abdominal diastasis (AD) is highly prevalent at post-partum. Although several conservative approaches have been proposed, an effective and protocolized treatment is lacking for this condition.
Objective: To ...
Grammar-based evolutionary approach for automated workflow composition with domain-specific operators and ensemble diversity
(Elsevier, 2024)
The process of extracting valuable and novel insights from raw data involves a series of complex steps. In the realm of Automated Machine Learning (AutoML), a significant research focus is on automating aspects of this ...