Machine learning in prediction of genetic risk of nonsyndromic oral clefts in the Brazilian population (2021)
- Authors:
- USP affiliated authors: NEVES, LUCIMARA TEIXEIRA DAS - FOB ; MACHADO, RENATO ASSIS - HRAC
- Unidades: FOB; HRAC
- DOI: 10.1007/s00784-020-03433-y
- Subjects: FISSURA LÁBIOPALATINA; POLIMORFISMO; APRENDIZADO COMPUTACIONAL; ACONSELHAMENTO GENÉTICO
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Clinical Oral Investigations
- ISSN: 1432-6981
- Volume/Número/Paginação/Ano: v. 25, n. 3, p. 1273-1280, Mar. 2021
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MACHADO, Renato Assis et al. Machine learning in prediction of genetic risk of nonsyndromic oral clefts in the Brazilian population. Clinical Oral Investigations, v. 25, n. 3, p. 1273-1280, 2021Tradução . . Disponível em: https://doi.org/10.1007/s00784-020-03433-y. Acesso em: 31 out. 2024. -
APA
Machado, R. A., Silva, C. de O., Martelli Júnior, H., Neves, L. T. das, & Coletta, R. D. (2021). Machine learning in prediction of genetic risk of nonsyndromic oral clefts in the Brazilian population. Clinical Oral Investigations, 25( 3), 1273-1280. doi:10.1007/s00784-020-03433-y -
NLM
Machado RA, Silva C de O, Martelli Júnior H, Neves LT das, Coletta RD. Machine learning in prediction of genetic risk of nonsyndromic oral clefts in the Brazilian population [Internet]. Clinical Oral Investigations. 2021 ; 25( 3): 1273-1280.[citado 2024 out. 31 ] Available from: https://doi.org/10.1007/s00784-020-03433-y -
Vancouver
Machado RA, Silva C de O, Martelli Júnior H, Neves LT das, Coletta RD. Machine learning in prediction of genetic risk of nonsyndromic oral clefts in the Brazilian population [Internet]. Clinical Oral Investigations. 2021 ; 25( 3): 1273-1280.[citado 2024 out. 31 ] Available from: https://doi.org/10.1007/s00784-020-03433-y - Identification of novel variants in cleft palate-associated genes in Brazilian patients with non-syndromic cleft palate only
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Informações sobre o DOI: 10.1007/s00784-020-03433-y (Fonte: oaDOI API)
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