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
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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: 12 jun. 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-zNLM
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 jun. 12 ] Available from: https://doi.org/10.1007/s41666-021-00100-zVancouver
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 jun. 12 ] Available from: https://doi.org/10.1007/s41666-021-00100-z
