Source: Clinical Cancer Research. Conference titles: San Antonio Breast Cancer Symposium. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, NEOPLASIAS MAMÁRIAS
ABNT
ROCHA, José Cláudio Casali da et al. Explainable machine learning reveals hidden hereditary risk of breast cancer beyond TP53: insights from Brazilian families with high prevalence of the p.R337H mutation. Clinical Cancer Research. Philadelphia: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1158/1557-3265.SABCS25-PS3-04-11. Acesso em: 06 maio 2026. , 2026APA
Rocha, J. C. C. da, Ricciardi, A. C. P., Pinheiro, G. B., Pegos, D. S., & Romero, R. A. F. (2026). Explainable machine learning reveals hidden hereditary risk of breast cancer beyond TP53: insights from Brazilian families with high prevalence of the p.R337H mutation. Clinical Cancer Research. Philadelphia: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1158/1557-3265.SABCS25-PS3-04-11NLM
Rocha JCC da, Ricciardi ACP, Pinheiro GB, Pegos DS, Romero RAF. Explainable machine learning reveals hidden hereditary risk of breast cancer beyond TP53: insights from Brazilian families with high prevalence of the p.R337H mutation [Internet]. Clinical Cancer Research. 2026 ; 32[citado 2026 maio 06 ] Available from: https://doi.org/10.1158/1557-3265.SABCS25-PS3-04-11Vancouver
Rocha JCC da, Ricciardi ACP, Pinheiro GB, Pegos DS, Romero RAF. Explainable machine learning reveals hidden hereditary risk of breast cancer beyond TP53: insights from Brazilian families with high prevalence of the p.R337H mutation [Internet]. Clinical Cancer Research. 2026 ; 32[citado 2026 maio 06 ] Available from: https://doi.org/10.1158/1557-3265.SABCS25-PS3-04-11
