Human vs Machine Towards Neonatal Pain Assessment: A Comparison of the Facial Features Extracted by Adults and Convolutional Neural Networks

  • Lucas Pereira Carlini FEI
  • Carlos Eduardo Thomaz FEI

Resumo


Recém-nascidos (RNs) em estado crítico ou prematuros passam diariamente por inúmeros procedimentos dolorosos, necessitando avaliação contínua da dor. No entanto, resultados recentes evidenciaram a subjetividade dos métodos aplicados por profissionais de saúde. Neste contexto, este trabalho aplica modelos computacionais para compreender de maneira específica a dor expressa por RNs, comparando as características faciais relevantes para a máquina com as regiões observadas por Médicos e Pais de RN durante avaliação da dor. Os resultados obtidos mostraram que as regiões relevantes para os modelos computacionais são clinicamente importantes e, em partes, concordam com a percepção facial humana.

Referências

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Publicado
27/06/2023
CARLINI, Lucas Pereira; THOMAZ, Carlos Eduardo. Human vs Machine Towards Neonatal Pain Assessment: A Comparison of the Facial Features Extracted by Adults and Convolutional Neural Networks. In: PRÊMIO ARTUR ZIVIANI - CONCURSO DE TESES E DISSERTAÇÕES (MESTRADO) - SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 23. , 2023, São Paulo/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 78-83. ISSN 2763-8987. DOI: https://doi.org/10.5753/sbcas_estendido.2023.229341.