Tuberculosis diagnosis support analysis for precarious health information systems.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Pulmonary tuberculosis is a world emergency for the World Health Organization. Techniques and new diagnosis tools are important to battle this bacterial infection. There have been many advances in all those fields, but in developing countries such as Colombia, where the resources and infrastructure are limited, new fast and less expensive strategies are increasingly needed. Artificial neural networks are computational intelligence techniques that can be used in this kind of problems and offer additional support in the tuberculosis diagnosis process, providing a tool to medical staff to make decisions about management of subjects under suspicious of tuberculosis.

Authors

  • Alvaro David Orjuela-Cañón
    Electronics and Biomedical Engineering Faculty, Universidad Antonio Nariño, Carrera 3 Este No. 47A - 15 Bloque 4 Piso 1, Bogota, D.C., Colombia. Electronic address: alvorjuela@uan.edu.co.
  • Jorge Eliécer Camargo Mendoza
    Systems Engineering Faculty, Universidad Antonio Nariño, Bogota, D.C., Colombia.
  • Carlos Enrique Awad García
    Tuberculosis Program, Santa Clara Hospital, Bogotá, D.C., Colombia.
  • Erika Paola Vergara Vela
    Tuberculosis Program, Santa Clara Hospital, Bogotá, D.C., Colombia.