Clinical and Social Characterization of Patients Hospitalized for COPD Exacerbation Using Machine Learning Tools.

Journal: Archivos de bronconeumologia
PMID: 39572361

Abstract

OBJECTIVE: This study aims to employ machine learning (ML) tools to cluster patients hospitalized for acute exacerbations of chronic obstructive pulmonary disease (COPD) based on their diverse social and clinical characteristics. This clustering is intended to facilitate the subsequent analysis of differences in clinical outcomes.

Authors

  • Manuel Casal-Guisande
    Department of Design in Engineering, University of Vigo, 36208 Vigo, Galicia, Spain.
  • Cristina Represas-Represas
    NeumoVigo I+i, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO , Spain; Pulmonary Department, Hospital Álvaro Cunqueiro (Vigo), Spain; Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Spain.
  • Rafael Golpe
    Pulmonary Department, Hospital Lucus Augusti (Lugo), Spain.
  • Alberto Fernández-García
    NeumoVigo I+i, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO , Spain; Department of Radiodiagnosis, Hospital Ribera POVISA (Vigo), Spain.
  • Almudena González-Montaos
    NeumoVigo I+i, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO , Spain; Pulmonary Department, Hospital Álvaro Cunqueiro (Vigo), Spain.
  • Alberto Comesaña-Campos
    Department of Design in Engineering, University of Vigo, 36208 Vigo, Galicia, Spain.
  • Alberto Ruano-Ravina
    Área de Medicina Preventiva y Salud Pública, Universidad de Santiago de Compostela, Servicio de Medicina Preventiva, Hospital Clínico Universitario de Santiago de Compostela, CIBER de Epidemiología y Salud Pública (CIBERESP), Santiago de Compostela, España.
  • Alberto Fernández-Villar
    Grupo NeumoVigo I + i, Instituto de Investigación Sanitaria Galicia Sur (IISGS), Servicio de Neumología, Hospital Álvaro Cunqueiro, Vigo, España.

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