Source: International Journal of Computer Assisted Radiology and Surgery. Conference titles: International Congress and Exhibition on Computer Assisted Radiology and Surgery - CARS. Unidade: FMRP
Subjects: DIAGNÓSTICO POR COMPUTADOR, APRENDIZADO COMPUTACIONAL, RADIOLOGIA, REUMATOLOGIA, RESSONÂNCIA MAGNÉTICA
ABNT
TENÓRIO, Ariane Priscilla Magalhães et al. Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s11548-020-02171-6. Acesso em: 27 set. 2024. , 2020APA
Tenório, A. P. M., Faleiros, M. C., Ferreira-Junior, J. R., Dalto, V. F., Assad, R. L., Nogueira-Barbosa, M. H., & Azevedo-Marques, P. M. de. (2020). Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences. International Journal of Computer Assisted Radiology and Surgery. Heidelberg: Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo. doi:10.1007/s11548-020-02171-6NLM
Tenório APM, Faleiros MC, Ferreira-Junior JR, Dalto VF, Assad RL, Nogueira-Barbosa MH, Azevedo-Marques PM de. Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S129-S130.[citado 2024 set. 27 ] Available from: https://doi.org/10.1007/s11548-020-02171-6Vancouver
Tenório APM, Faleiros MC, Ferreira-Junior JR, Dalto VF, Assad RL, Nogueira-Barbosa MH, Azevedo-Marques PM de. Machine learning models to predict axial and peripheral spondyloarthritis: a comparative radiomic study between SPAIR and STIR MRI sequences [Internet]. International Journal of Computer Assisted Radiology and Surgery. 2020 ; 15 S129-S130.[citado 2024 set. 27 ] Available from: https://doi.org/10.1007/s11548-020-02171-6