Kambeitz, Joseph; Goerigk, Stephan; Gattaz, Wagner Farid 
; Falkai, Peter; Benseñor, Isabela Judith Martins ; Lotufo, Paulo Andrade ; Buehner, Markus; Koutsouleris, Nikolaos; Padberg, Frank; Brunoni, Andre Russowsky
Source: Journal of affective disorders. Unidade: FM
Subjects: DEPRESSÃO, PSICOTERAPIA, CÓRTEX PRÉ-FRONTAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
KAMBEITZ, Joseph et al. Clinical patterns differentially predict response to transcranial direct current stimulation (tDCS) and escitalopram in major depression: a machine learning analysis of the ELECT-TDCS study. Journal of affective disorders, v. 265, p. 460-467, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.jad.2020.01.118. Acesso em: 01 nov. 2024.APA
Kambeitz, J., Goerigk, S., Gattaz, W. F., Falkai, P., Benseñor, I. J. M., Lotufo, P. A., et al. (2020). Clinical patterns differentially predict response to transcranial direct current stimulation (tDCS) and escitalopram in major depression: a machine learning analysis of the ELECT-TDCS study. Journal of affective disorders, 265, 460-467. doi:10.1016/j.jad.2020.01.118NLM
Kambeitz J, Goerigk S, Gattaz WF, Falkai P, Benseñor IJM, Lotufo PA, Buehner M, Koutsouleris N, Padberg F, Brunoni AR. Clinical patterns differentially predict response to transcranial direct current stimulation (tDCS) and escitalopram in major depression: a machine learning analysis of the ELECT-TDCS study [Internet]. Journal of affective disorders. 2020 ; 265 460-467.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.jad.2020.01.118Vancouver
Kambeitz J, Goerigk S, Gattaz WF, Falkai P, Benseñor IJM, Lotufo PA, Buehner M, Koutsouleris N, Padberg F, Brunoni AR. Clinical patterns differentially predict response to transcranial direct current stimulation (tDCS) and escitalopram in major depression: a machine learning analysis of the ELECT-TDCS study [Internet]. Journal of affective disorders. 2020 ; 265 460-467.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.jad.2020.01.118
