Source: Antibiotics. Unidade: IFSC
Subjects: RESISTÊNCIA MICROBIANA ÀS DROGAS, ANTIBIÓTICOS, APRENDIZADO COMPUTACIONAL
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PATIÑO, Claudia Patricia Barrera et al. Spectroscopic identification of bacteria resistance to antibiotics by means of absorption of specific biochemical groups and special machine learning algorithm. Antibiotics, v. 12, n. 10, p. 1502-1-1502-18 + supplementary materials, 2023Tradução . . Disponível em: https://doi.org/10.3390/antibiotics12101502. Acesso em: 01 set. 2024.APA
Patiño, C. P. B., Soares, J. M., Blanco, K. C., Inada, N. M., & Bagnato, V. S. (2023). Spectroscopic identification of bacteria resistance to antibiotics by means of absorption of specific biochemical groups and special machine learning algorithm. Antibiotics, 12( 10), 1502-1-1502-18 + supplementary materials. doi:10.3390/antibiotics12101502NLM
Patiño CPB, Soares JM, Blanco KC, Inada NM, Bagnato VS. Spectroscopic identification of bacteria resistance to antibiotics by means of absorption of specific biochemical groups and special machine learning algorithm [Internet]. Antibiotics. 2023 ; 12( 10): 1502-1-1502-18 + supplementary materials.[citado 2024 set. 01 ] Available from: https://doi.org/10.3390/antibiotics12101502Vancouver
Patiño CPB, Soares JM, Blanco KC, Inada NM, Bagnato VS. Spectroscopic identification of bacteria resistance to antibiotics by means of absorption of specific biochemical groups and special machine learning algorithm [Internet]. Antibiotics. 2023 ; 12( 10): 1502-1-1502-18 + supplementary materials.[citado 2024 set. 01 ] Available from: https://doi.org/10.3390/antibiotics12101502