Predicting Brain Age at Slice Level : Convolutional Neural Networks and Consequences for Interpretability

Ballester, Pedro L.da Silva, Laura TomazMarcon, MatheusEsper, Nathalia BianchiniFrey, Benicio N.Buchweitz, AugustoMeneguzzi, Felipe2023-03-202023-03-202021-02-25Ballester, P L, da Silva, L T, Marcon, M, Esper, N B, Frey, B N, Buchweitz, A & Meneguzzi, F 2021, 'Predicting Brain Age at Slice Level : Convolutional Neural Networks and Consequences for Interpretability', Frontiers in psychiatry, vol. 12, 598518. https://doi.org/10.3389/fpsyt.2021.5985181664-0640ORCID: /0000-0003-3549-6168/work/131351724https://hdl.handle.net/2164/20309Funding Information: NE was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior— Brasil (CAPES)—Finance Code 001. MM was financed in part by the Conselho Nacional de Pesquisa—Brasil (CNPq). Funding Information: Conflict of Interest: BF had a research grant from Pfizer outside of this study.122195075engSDG 3 - Good Health and Well-beingbrain ageconvolutional neural networksdeep learningmodel interpretabilityneuroimagingR MedicinePsychiatry and Mental healthSupplementary DataRPredicting Brain Age at Slice Level : Convolutional Neural Networks and Consequences for InterpretabilityJournal article10.3389/fpsyt.2021.598518https://www.scopus.com/pages/publications/85102461282