A proposal for automatic diagnosis of malaria: extended abstract

  • Authors:

  • Allisson D. Oliveira;Giordano Cabral;D. López;Caetano Firmo;F. Zarzuela Serrat;J. Albuquerque

  • Affiliations:

  • University Federal Rural of Pernambuco, Recife, Brazil;University Federal Rural of Pernambuco, Recife, Brazil;Universitat Politécnica de Catalunya, Barcelona, Spain;University Federal Rural of Pernambuco, Recife, Brazil;Institut Català de la Salut (ICS), Barcelona, Spain;University Federal Rural of Pernambuco, Recife, Brazil

  • Venue:
  • Proceedings of the 22nd international conference on World Wide Web companion
  • Year:
  • 2013

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Abstract

This paper presents a methodology for automatic diagnosis of malaria using computer vision techniques combined with artificial intelligence. We had obtained an accuracy rate of 74% in the detection system.