Source: International Journal of Radiation Oncology*Biology*Physics. Unidade: FFCLRP
Subjects: CÁRIE DENTÁRIA, RADIOTERAPIA, NEOPLASIAS CEREBRAIS
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NEVES, L. V. F. et al. Feasibility of prediction of radiation-related caries in head-neck cancer patients using machine learning and radiomics features. International Journal of Radiation Oncology*Biology*Physics, v. 108, n. 3, p. e782, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijrobp.2020.07.243. Acesso em: 08 set. 2024.APA
Neves, L. V. F., Danelichen, A. F. B., Faustino, A., Matsuura, F. K., Viani, G., Azimbagirad, M., et al. (2020). Feasibility of prediction of radiation-related caries in head-neck cancer patients using machine learning and radiomics features. International Journal of Radiation Oncology*Biology*Physics, 108( 3), e782. doi:10.1016/j.ijrobp.2020.07.243NLM
Neves LVF, Danelichen AFB, Faustino A, Matsuura FK, Viani G, Azimbagirad M, Faria VDA, Pavoni JF, Felipe JC, Murta Júnior LO. Feasibility of prediction of radiation-related caries in head-neck cancer patients using machine learning and radiomics features [Internet]. International Journal of Radiation Oncology*Biology*Physics. 2020 ; 108( 3): e782.[citado 2024 set. 08 ] Available from: https://doi.org/10.1016/j.ijrobp.2020.07.243Vancouver
Neves LVF, Danelichen AFB, Faustino A, Matsuura FK, Viani G, Azimbagirad M, Faria VDA, Pavoni JF, Felipe JC, Murta Júnior LO. Feasibility of prediction of radiation-related caries in head-neck cancer patients using machine learning and radiomics features [Internet]. International Journal of Radiation Oncology*Biology*Physics. 2020 ; 108( 3): e782.[citado 2024 set. 08 ] Available from: https://doi.org/10.1016/j.ijrobp.2020.07.243