FTIR-derived feature insights for predicting time-dependent antibiotic resistance progression (2025)
- Authors:
- USP affiliated authors: BLANCO, KATE CRISTINA - IFSC ; BAGNATO, VANDERLEI SALVADOR - IFSC ; PATIÑO, CLAUDIA PATRICIA BARRERA - IFSC ; SOARES, JENNIFER MACHADO - IFSC
- Unidade: IFSC
- DOI: 10.3390/antibiotics14080831
- Subjects: ANTIBIÓTICOS; TERAPIA FOTODINÂMICA; RESISTÊNCIA MICROBIANA ÀS DROGAS
- Keywords: Antibiotic-resistant bacteria; Prediction model; Staphylococcus aureus
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Antibiotics
- ISSN: 2079-6382
- Volume/Número/Paginação/Ano: v. 14, n. 8, p. 831-1-831-22 + supplementary material, Aug. 2025
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
BONNER, Mitchell et al. FTIR-derived feature insights for predicting time-dependent antibiotic resistance progression. Antibiotics, v. 14, n. 8, p. 831-1-831-22 + supplementary material, 2025Tradução . . Disponível em: https://doi.org/10.3390/antibiotics14080831. Acesso em: 11 fev. 2026. -
APA
Bonner, M., Patiño, C. P. B., Borsatto, A. R., Soares, J. M., Blanco, K. C., & Bagnato, V. S. (2025). FTIR-derived feature insights for predicting time-dependent antibiotic resistance progression. Antibiotics, 14( 8), 831-1-831-22 + supplementary material. doi:10.3390/antibiotics14080831 -
NLM
Bonner M, Patiño CPB, Borsatto AR, Soares JM, Blanco KC, Bagnato VS. FTIR-derived feature insights for predicting time-dependent antibiotic resistance progression [Internet]. Antibiotics. 2025 ; 14( 8): 831-1-831-22 + supplementary material.[citado 2026 fev. 11 ] Available from: https://doi.org/10.3390/antibiotics14080831 -
Vancouver
Bonner M, Patiño CPB, Borsatto AR, Soares JM, Blanco KC, Bagnato VS. FTIR-derived feature insights for predicting time-dependent antibiotic resistance progression [Internet]. Antibiotics. 2025 ; 14( 8): 831-1-831-22 + supplementary material.[citado 2026 fev. 11 ] Available from: https://doi.org/10.3390/antibiotics14080831 - Time evolution of bacterial resistance observed with principal component analysis
- Machine learning in FTIR spectrum for the identification of antibiotic resistance: a demonstration with different species of microorganisms
- Identification of antibiotic resistance in FTIR spectra of bacteria with machine learning algorithms
- Identification of antibiotic resistance susceptibility in different species of microorganisms implementing machine learning
- Spectroscopic identification of bacteria resistance to antibiotics by means of absorption of specific biochemical groups and special machine learning algorithm
- Implementation of machine learning study in Staphylococcus aureus’s FTIR spectra to antibiotic resistance identification
- Combinação de antibiótico com inativação fotodinâmica para o tratamento de infecções bacterianas
- Antibiotic combination with photodynamic inactivation for the treatment of bacterial infections
- Ação da inativação fotodinâmica nas falhas de antibiótico
- Synergistic enhancement effects of antibiotic combination with photodynamic inactivation
Informações sobre o DOI: 10.3390/antibiotics14080831 (Fonte: oaDOI API)
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