Thesis Collection
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Browsing by Author "Domínguez Olmedo, Juan Luis"
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A Rule-based Method Applied to the Imbalanced Classification of Radiation Toxicity
Domínguez Olmedo, Juan Luis
; Mata Vázquez, Jacinto; Pachón Álvarez, Victoria; López Guerra, José L. (Science and Technology Publications, 2018)
This paper describes a rule-based classifier (DEQAR-C), which is set up by the combination of selected rules after a two-phase process. In the first phase, the rules are generated and sorted for each class, and then a ... -
Age-Stratified Analysis of COVID-19 Outcome Using Machine Learning Predictive Models
Domínguez Olmedo, Juan Luis; Gragera Martínez, Álvaro; Mata Vázquez, Jacinto; Pachón Álvarez, Victoria (MDPI, 2022-10)
Since the emergence of COVID-19, most health systems around the world have experienced a series of spikes in the number of infected patients, leading to collapse of the health systems in many countries. The use of clinical ... -
Machine Learning Applied to Clinical Laboratory Data in Spain for COVID-19 Outcome Prediction: Model Development and Validation
Domínguez Olmedo, Juan Luis; Gragera Martínez, Álvaro; Mata Vázquez, Jacinto; Pachón Álvarez, Victoria (2021-04-14)
Background: The COVID-19 pandemic is probably the greatest health catastrophe of the modern era. Spain’s health care system has been exposed to uncontrollable numbers of patients over a short period, causing the system to ... -
Una propuesta determinista para la obtención de reglas en problemas de minería de datos
Domínguez Olmedo, Juan Luis (Universidad de Huelva, 2019)
En esta tesis se describen con detalle los trabajos realizados para afrontar, mediante un nuevo enfoque determinista, la generación de reglas para su aplicación a problemas de minería de datos. Concretamente, y dado que ... -
Rule extraction from medical data without discretization of numerical attributes
Domínguez Olmedo, Juan Luis; Mata Vázquez, Jacinto; Pachón Álvarez, Victoria; Maña López, Manuel Jesús (Science and Technology Publications, 2012)
Association rule mining is a popular technique used to find associations between attributes in a dataset. When using deterministic algorithms, if the attributes have numerical values the usual approach is to discretize ...
