Browsing by Author "Gutiérrez J."

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Differential diagnosis of dengue and chikungunya in colombian children using machine learning
(Springer Verlag, 2018) Caicedo-Torres W.; Paternina-Caicedo Á.; Pinzón-Redondo H.; Gutiérrez J.; Ferme E.; Simari G.R.; Gutierrez Segura F.; Rodriguez Melquiades J.A.
Dengue and chikungunya are vector borne diseases endemic in tropical countries around the world, with very similar clinical presentation, which makes it hard for physicians to tell them apart. Here we propose the use of Machine Learning based classifiers to perform differential diagnosis of dengue and chikungunya in pediatric patients, using simple blood test results as predictors instead of symptoms. Three variables (platelet count, white cell count and hematocrit percentage) from 447 pediatric patients from Hospital Infantil Napoleón Franco Pareja were collected to construct a dataset, later partitioned into train and test sets using Stratified Random Sampling. Grid Search with Stratified 5-Fold Cross-Validation was conducted to assess the performance of Logistic Regression, Support Vector Machine, and CART Decision Tree classifiers. Cross-Validation results show a L2 Logistic Regression model with second degree polynomial features outperforming the other models considered, with a cross-validated Receiver Operating Characteristic Area Under the Curve (ROC AUC) score of 0.8694. Subsequent results over the test set showed a 0.8502 ROC AUC score. Despite a reduced sample and a heavily imbalanced data set, ROC AUC score results are promising and support our approach for dengue and chikungunya differential diagnosis. © Springer Nature Switzerland AG 2018.
Technology and market conditions toward a new competitive landscape in the wireless access market
(2010) Beltrán F.; Gutiérrez J.; Melus J.L.
This article argues that the wireless telecommunication market is about to witness a shift in business models and market structure as a result of the deployment of new broadband access technologies, spectrum management techniques, policy-based network management, and the drive of new entrants to compete against the incumbents. The article discusses four agents of evolutionary changes: a range of broadband wireless access standards and technologies that are frontrunners in the industry's efforts to embody the next generation of wireless networks; new provider-customer relationships facilitated through changes in the usual contract patterns that will allow consumers to enter short-term and spot contracts with the new wireless providers; an overview of the current debate on spectrum management; and an explanation of how autonomic communications and policybased management would support the new structure. Finally, the article asserts the necessity for the integration of the heterogeneous technologies that make up this emerging, hybrid wireless landscape, and describes the economic characteristics of a new competitive scenario. © 2010 IEEE.