Source: Schizophrenia research. Unidade: FM
Subjects: TRANSTORNOS PSICÓTICOS, APRENDIZADO COMPUTACIONAL
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ABNT
LOCH, Alexandre Andrade et al. Detecting at-risk mental states for psychosis (ARMS) using machine learning ensembles and facial features. Schizophrenia research, v. 258, p. 45-52, 2023Tradução . . Disponível em: https://observatorio.fm.usp.br/handle/OPI/56176. Acesso em: 03 nov. 2024.APA
Loch, A. A., Gondim, J. M., Argolo, F. C., Rocha, A. C. L., Andrade, J. C. D. de, Bilt, M. T. van de, et al. (2023). Detecting at-risk mental states for psychosis (ARMS) using machine learning ensembles and facial features. Schizophrenia research, 258, 45-52. doi:10.1016/j.schres.2023.07.011NLM
Loch AA, Gondim JM, Argolo FC, Rocha ACL, Andrade JCD de, Bilt MT van de, Jesus LP de, Santos NMH de O, Cecchi GA, Mota NB, Gattaz WF, Corcoran CM, Souza ALA. Detecting at-risk mental states for psychosis (ARMS) using machine learning ensembles and facial features [Internet]. Schizophrenia research. 2023 ; 258 45-52.[citado 2024 nov. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/56176Vancouver
Loch AA, Gondim JM, Argolo FC, Rocha ACL, Andrade JCD de, Bilt MT van de, Jesus LP de, Santos NMH de O, Cecchi GA, Mota NB, Gattaz WF, Corcoran CM, Souza ALA. Detecting at-risk mental states for psychosis (ARMS) using machine learning ensembles and facial features [Internet]. Schizophrenia research. 2023 ; 258 45-52.[citado 2024 nov. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/56176