Machine learning used to create a multidimensional calibration space for sensing and biosensing data (2021)
- Authors:
- USP affiliated authors: OLIVEIRA JUNIOR, OSVALDO NOVAIS DE - IFSC ; PAULOVICH, FERNANDO VIEIRA - ICMC ; POPOLIN NETO, MÁRIO - ICMC
- Unidades: IFSC; ICMC
- DOI: 10.1246/bcsj.20200359
- Subjects: BIOTECNOLOGIA; APRENDIZADO COMPUTACIONAL; SENSOR; FILMES FINOS
- Keywords: Machine learning; Interpretable artificial intelligence; Sensors classification model
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Bulletin of the Chemical Society of Japan
- ISSN: 0009-2673
- Volume/Número/Paginação/Ano: v. 94, n. 5, p. 1553-1562, May 2021
- Status:
- Artigo possui versão em acesso aberto em repositório (Green Open Access)
- Versão do Documento:
- Versão submetida (Pré-print)
- Acessar versão aberta:
-
ABNT
POPOLIN NETO, Mário et al. Machine learning used to create a multidimensional calibration space for sensing and biosensing data. Bulletin of the Chemical Society of Japan, v. 94, n. 5, p. 1553-1562, 2021Tradução . . Disponível em: https://doi.org/10.1246/bcsj.20200359. Acesso em: 01 abr. 2026. -
APA
Popolin Neto, M., Soares, A. C., Oliveira Junior, O. N. de, & Paulovich, F. V. (2021). Machine learning used to create a multidimensional calibration space for sensing and biosensing data. Bulletin of the Chemical Society of Japan, 94( 5), 1553-1562. doi:10.1246/bcsj.20200359 -
NLM
Popolin Neto M, Soares AC, Oliveira Junior ON de, Paulovich FV. Machine learning used to create a multidimensional calibration space for sensing and biosensing data [Internet]. Bulletin of the Chemical Society of Japan. 2021 ; 94( 5): 1553-1562.[citado 2026 abr. 01 ] Available from: https://doi.org/10.1246/bcsj.20200359 -
Vancouver
Popolin Neto M, Soares AC, Oliveira Junior ON de, Paulovich FV. Machine learning used to create a multidimensional calibration space for sensing and biosensing data [Internet]. Bulletin of the Chemical Society of Japan. 2021 ; 94( 5): 1553-1562.[citado 2026 abr. 01 ] Available from: https://doi.org/10.1246/bcsj.20200359 - Explainable matrix: visualization for global and local interpretability of random forest classification ensembles
- Detection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space
- Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models
- Investigating band gap directness using machine learning
- Thin film composition and solution characteristics: on the role played in electronic tongues
- Herbicide detection using surface-enhanced raman scattering and impedance spectroscopy
- Impedance electrical immunosensor for hepatitis C diagnostics based on biorecognition between the antigenic peptide NS5A-1 and the antibody anti-HCV
- Detection of trace levels of atrazine using surface-enhanced Raman scattering and information visualization
- On the distinct molecular architectures of dipping- and spray-LbL films containing lipid vesicles
- Molecularly-designed layer-by-layer (LbL) films to detect catechol using information visualization methods
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Por se tratar de integração com serviço externo, podem existir diferentes versões do trabalho (como preprints ou postprints), que podem diferir da versão publicada.
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3033272.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
