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Filtros : "REDES NEURAIS" "Financiamento MIAI" Limpar

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  • Artigo de periodico

    DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification (2021)

    Lima, Daniel Mário de ; Rodrigues Junior, José Fernando ; Machado, Bruno Brandoli ; Goeuriot, Lorraine ; Amer-Yahia, Sihem

    Source: SN Computer Science. Unidade: ICMC

    Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, NEOPLASIAS CUTÂNEAS, MELANOMA

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      LIMA, Daniel Mário de et al. DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification. SN Computer Science, v. 2, n. 4, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1007/s42979-021-00641-5. Acesso em: 03 nov. 2024.

    • APA

      Lima, D. M. de, Rodrigues Junior, J. F., Machado, B. B., Goeuriot, L., & Amer-Yahia, S. (2021). DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification. SN Computer Science, 2( 4), 1-13. doi:10.1007/s42979-021-00641-5

    • NLM

      Lima DM de, Rodrigues Junior JF, Machado BB, Goeuriot L, Amer-Yahia S. DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification [Internet]. SN Computer Science. 2021 ; 2( 4): 1-13.[citado 2024 nov. 03 ] Available from: https://doi.org/10.1007/s42979-021-00641-5

    • Vancouver

      Lima DM de, Rodrigues Junior JF, Machado BB, Goeuriot L, Amer-Yahia S. DermaDL: advanced convolutional neural networks for computer-aided skin-lesion classification [Internet]. SN Computer Science. 2021 ; 2( 4): 1-13.[citado 2024 nov. 03 ] Available from: https://doi.org/10.1007/s42979-021-00641-5

  • Artigo de periodico

    Real-world patient trajectory prediction from clinical notes using artificial neural networks and UMLS-based extraction of concepts (2021)

    Zaghir, Jamil ; Rodrigues Junior, José Fernando ; Goeuriot, Lorraine ; Amer-Yahia, Sihem

    Source: Journal of Healthcare Informatics Research. Unidade: ICMC

    Subjects: REDES NEURAIS, TECNOLOGIAS DA SAÚDE, PROGNÓSTICO

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      ZAGHIR, Jamil et al. Real-world patient trajectory prediction from clinical notes using artificial neural networks and UMLS-based extraction of concepts. Journal of Healthcare Informatics Research, v. 5, n. 4, p. 474-496, 2021Tradução . . Disponível em: https://doi.org/10.1007/s41666-021-00100-z. Acesso em: 03 nov. 2024.

    • APA

      Zaghir, J., Rodrigues Junior, J. F., Goeuriot, L., & Amer-Yahia, S. (2021). Real-world patient trajectory prediction from clinical notes using artificial neural networks and UMLS-based extraction of concepts. Journal of Healthcare Informatics Research, 5( 4), 474-496. doi:10.1007/s41666-021-00100-z

    • NLM

      Zaghir J, Rodrigues Junior JF, Goeuriot L, Amer-Yahia S. Real-world patient trajectory prediction from clinical notes using artificial neural networks and UMLS-based extraction of concepts [Internet]. Journal of Healthcare Informatics Research. 2021 ; 5( 4): 474-496.[citado 2024 nov. 03 ] Available from: https://doi.org/10.1007/s41666-021-00100-z

    • Vancouver

      Zaghir J, Rodrigues Junior JF, Goeuriot L, Amer-Yahia S. Real-world patient trajectory prediction from clinical notes using artificial neural networks and UMLS-based extraction of concepts [Internet]. Journal of Healthcare Informatics Research. 2021 ; 5( 4): 474-496.[citado 2024 nov. 03 ] Available from: https://doi.org/10.1007/s41666-021-00100-z
  • 1

1 - 2 (2 records)

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