Artificial intelligence on the identification of risk groups for osteoporosis, a general review.

Journal: Biomedical engineering online
Published Date: Jan 29, 2018

Abstract

INTRODUCTION: The goal of this paper is to present a critical review on the main systems that use artificial intelligence to identify groups at risk for osteoporosis or fractures. The systems considered for this study were those that fulfilled the following requirements: range of coverage in diagnosis, low cost and capability to identify more significant somatic factors.

Authors

  • Agnaldo S Cruz
    Centro de Tecnologia, Universidade Federal do Rio Grande do Norte UFRN, Av. Salgado Filho, Natal, Brazil. agnaldo@ct.ufrn.br.
  • Hertz C Lins
    Laboratory of Technological Innovation in Healthcare, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil.
  • Ricardo V A Medeiros
    Laboratory of Technological Innovation in Healthcare, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil.
  • José M F Filho
    Laboratory of Technological Innovation in Healthcare, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil.
  • Sandro G da Silva
    Centro de Tecnologia, Universidade Federal do Rio Grande do Norte UFRN, Av. Salgado Filho, Natal, Brazil.

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