• Title of article

    Analysis of Medical Opinions about the Nonrealization of Autopsies in a Mexican Hospital Using Association Rules and Bayesian Networks

  • Author/Authors

    Delgado,Elayne Rubio Division de Estudios de Posgrado e Investigaci ´ on - Instituto Tecnol ´ ogico de Orizaba, Orizaba, VER, Mexico , Rodríguez-Mazahua, Lisbeth Division de Estudios de Posgrado e Investigaci ´ on - Instituto Tecnol ´ ogico de Orizaba, Orizaba, VER, Mexico , Palet Guzmán,José Antonio Hospital Regional de R´ıo Blanco (HRRB), R´ıo Blanco, VER, Mexico , Cervantes,Jair 3 Universidad Autonoma del Estado de M ´ exico - Centro Universitario UAEM Texcoco, Texcoco, MEX, Mexico , Cervantes, José Luis Sánchez CONACYT-Instituto Tecnologico de Orizaba, Orizaba, VER, Mexico , Camarena, Silvestre Gustavo Peláez Division de Estudios de Posgrado e Investigaci ´ on - Instituto Tecnol ´ ogico de Orizaba, Orizaba, VER, Mexico , López-Chau, Asdrúbal Universidad Autonoma del Estado de M ´ exico - Centro Universitario UAEM Zumpango, Zumpango, MEX, Mexico

  • Pages
    22
  • From page
    1
  • To page
    22
  • Abstract
    This research identifies the factors influencing the reduction of autopsies in a hospital of Veracruz. The study is based on the application of data mining techniques such as association rules and Bayesian networks in data sets obtained from opinions of physicians. We analyzed, for the exploration and extraction of the knowledge, algorithms like Apriori, FPGrowth, PredictiveApriori, Tertius, J48, NaiveBayes, MultilayerPerceptron, and BayesNet, all of them provided by the API of WEKA. To generate mining models and present the new knowledge in natural language, we also developed a web application. The results presented in this study are those obtained from the best-evaluated algorithms, which have been validated by specialists in the field of pathology. 1. Intro
  • Keywords
    Bayesian Networks , Analysis , Medical Opinions , Mexican Hospital Using , Bayesian Networks
  • Journal title
    Scientific Programming
  • Serial Year
    2018
  • Record number

    2609375