Um Modelo para Predição Individualizada da Deterioração da Saúde de Pacientes no âmbito da Internet das Coisas

  • Naira Kaieski UNISINOS
  • Diogo Schmidt UNISINOS
  • Carolina Kelsh UNISINOS
  • Denise Silva UNISINOS
  • Cristiano Costa UNISINOS
  • Rodrigo Righi UNISINOS


Este artigo apresenta o desenvolvimento de um modelo baseado em internet das coisas de saúde e inteligência artificial para prever a deterioração do estado de saúde de pacientes. Foi construído um modelo de Deep Learning baseado em Redes Neurais Convolucionais para processar os dados que podem ser coletados por sensores ubíquos. Foram utilizadas duas estratégias diferentes para treinar o modelo, uma baseada na abordagem populacional tradicional e outra mais individualizada onde os dados de treinamento são oriundos de pacientes similares em termos de idade ao indivíduo monitorado. Os resultados mostraram uma sensível melhora na acurácia da predição de mortalidade do modelo individualizado com AUC média de 0,73 para todas as faixas de idade enquanto o modelo populacional apresentou AUC de 0,70.


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KAIESKI, Naira; SCHMIDT, Diogo; KELSH, Carolina; SILVA, Denise; COSTA, Cristiano; RIGHI, Rodrigo . Um Modelo para Predição Individualizada da Deterioração da Saúde de Pacientes no âmbito da Internet das Coisas. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 20. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 167-178. ISSN 2763-8952. DOI:

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