Electrochemical and optical detection and machine learning applied to images of genosensors for diagnosis of prostate cancer with the biomarker PCA3 (2021)
- Authors:
- Rodrigues, Valquiria Cruz
- Soares, Juliana Coatrini - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
- Soares, Andrey Coatrini - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
- Braz, Daniel César
- Melendez, Matias Eliseo - Hospital de Câncer de Barretos (HCB)
- Ribas, Lucas Correia
- Scabini, Leonardo Felipe dos Santos
- Bruno, Odemir Martinez
- Carvalho, Andre Lopes - Hospital de Câncer de Barretos (HCB)
- Reis, Rui Manuel
- Sanfelice, Rafaela Cristina - Universidade Federal do Triângulo Mineiro (UFTM)
- Oliveira Junior, Osvaldo Novais de
- USP affiliated authors: BRUNO, ODEMIR MARTINEZ - IFSC ; OLIVEIRA JUNIOR, OSVALDO NOVAIS DE - IFSC ; BARIOTO, VALQUIRIA DA CRUZ RODRIGUES - IFSC ; SOARES, JULIANA COATRINI - IFSC ; BRAZ, DANIEL CESAR - IFSC ; RIBAS, LUCAS CORREIA - ICMC ; SCABINI, LEONARDO FELIPE DOS SANTOS - IFSC
- Unidades: IFSC; ICMC
- DOI: 10.1016/j.talanta.2020.121444
- Subjects: CELULOSE; SENSORES BIOMÉDICOS; BIOMARCADORES; NEOPLASIAS PROSTÁTICAS
- Keywords: Prostate cancer; PCA3 biomarker; Electrochemical impedance; Image analysis; Machine learning
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: hybrid
- Licença: publisher-specific-oa
-
ABNT
RODRIGUES, Valquiria Cruz et al. Electrochemical and optical detection and machine learning applied to images of genosensors for diagnosis of prostate cancer with the biomarker PCA3. Talanta, v. 222, n. Ja 2021, p. 121444-1-121444-10, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.talanta.2020.121444. Acesso em: 19 mar. 2024. -
APA
Rodrigues, V. C., Soares, J. C., Soares, A. C., Braz, D. C., Melendez, M. E., Ribas, L. C., et al. (2021). Electrochemical and optical detection and machine learning applied to images of genosensors for diagnosis of prostate cancer with the biomarker PCA3. Talanta, 222( Ja 2021), 121444-1-121444-10. doi:10.1016/j.talanta.2020.121444 -
NLM
Rodrigues VC, Soares JC, Soares AC, Braz DC, Melendez ME, Ribas LC, Scabini LF dos S, Bruno OM, Carvalho AL, Reis RM, Sanfelice RC, Oliveira Junior ON de. Electrochemical and optical detection and machine learning applied to images of genosensors for diagnosis of prostate cancer with the biomarker PCA3 [Internet]. Talanta. 2021 ; 222( Ja 2021): 121444-1-121444-10.[citado 2024 mar. 19 ] Available from: https://doi.org/10.1016/j.talanta.2020.121444 -
Vancouver
Rodrigues VC, Soares JC, Soares AC, Braz DC, Melendez ME, Ribas LC, Scabini LF dos S, Bruno OM, Carvalho AL, Reis RM, Sanfelice RC, Oliveira Junior ON de. Electrochemical and optical detection and machine learning applied to images of genosensors for diagnosis of prostate cancer with the biomarker PCA3 [Internet]. Talanta. 2021 ; 222( Ja 2021): 121444-1-121444-10.[citado 2024 mar. 19 ] Available from: https://doi.org/10.1016/j.talanta.2020.121444 - Análise exploratória de imagens do biossensor aplicado ao diagnóstico de câncer de próstata
- Deep topological embedding with convolutional neural networks for complex network classification
- Fusion of complex networks and randomized neural networks for texture analysis
- Detection of HPV16 in cell lines deriving from cervical and head and neck cancer using a genosensor made with a DNA probe on a layer-by-layer matrix
- Spatio-spectral networks for color-texture analysis
- A complex network approach for fish species recognition based on otolith shape
- Detection of Staphylococcus aureus in cattles with mastitis diseases based on electrical impedance measurements
- Machine learning and image processing to monitor strain and tensile forces with mechanochromic sensors
- Filmes automontados por adsorção física
- Evaluating deep convolutional neural networks as texture feature extractors
Informações sobre o DOI: 10.1016/j.talanta.2020.121444 (Fonte: oaDOI API)
Download do texto completo
Tipo | Nome | Link | |
---|---|---|---|
3003245.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas