Prediction of pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II based on clinical risk.

Journal: PloS one
PMID: 38833461

Abstract

OBJECTIVE: To assess the effectiveness of different machine learning models in estimating the pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II diagnosis, based on the clinical risk index determined by the analysis of comorbidities.

Authors

  • Javier-Leonardo Gonzalez-Rodriguez
    School of Management and Business, Universidad del Rosario, Bogotá, Colombia.
  • Carlos Franco
    School of Management and Business, Universidad del Rosario, Bogotá, Colombia.
  • Olga Pinzón-Espitia
    Facultad de Medicina, Departamento de Nutrición Humana, Universidad Nacional de Colombia, Hospital de la Misericordia, Universidad Del Rosario, Bogotá, Colombia.
  • Vicent Caballer
    Finanzas Empresariales, Universidad de Valencia, Valencia, Spain.
  • Edgar Alfonso-Lizarazo
    Université Jean Monnet Saint-Étienne, LASPI, Saint-Étienne, France.
  • Vincent Augusto
    Mines Saint-Etienne, Univ Clermont Auvergne INP Clermont Auvergne, CNRS, LIMOS Centre CIS, Saint-Etienne, France.

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