| Texto completo | |
| Autor(es): |
Neto, Mario Popolin
[1, 2]
;
Soares, Andrey Coatrini
[3]
;
Oliveira Jr, Osvaldo N.
;
Paulovich, V, Fernando
Número total de Autores: 4
|
| Afiliação do(s) autor(es): | [1] Fed Inst Sao Paulo IFSP, BR-14804296 Araraquara, SP - Brazil
[2] V, Univ Sao Paulo, Inst Math & Comp Sci ICMC, BR-13566590 Sao Carlos - Brazil
[3] Embrapa Instrumentacao, Nanotechnol Natl Lab Agr LNNA, BR-13560970 Sao Carlos, SP - Brazil
Número total de Afiliações: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN; v. 94, n. 5, p. 1553-1562, MAY 2021. |
| Citações Web of Science: | 0 |
| Resumo | |
Calibration curves are essential constructs in analytical chemistry to determine parameters of sensing performance. In the classification of sensing data of complex samples without a clear dependence on a given analyte, however, establishing a calibration curve is not possible. In this paper we introduce the concept of a multidimensional calibration space, which could serve as reference to classify any unknown sample as in determining an analyte concentration from a calibration curve. This calibration space is defined from a set of rules generated using a machine learning method based on trees applied to the dataset. The number of attributes employed in the rules defines the dimension of the calibration space and is established to warrant full coverage of the dataset. We demonstrate the calibration space concept with impedance spectroscopy data from sensors, biosensors and an e-tongue, but the concept can be extended to any type of sensing data and classification task. Using the calibration space should allow for the correct classification of unknown samples, provided that the data used to generate rules via machine learning can cover the whole range of sensing measurements. Furthermore, an inspection in the rules can assist in the design of sensing systems for optimized performance. (AU) | |
| Processo FAPESP: | 18/18953-8 - Filmes nanoestruturados aplicados em biossensores microfluídicos para detecção de mastite bacteriana |
| Beneficiário: | Andrey Coatrini Soares |
| Modalidade de apoio: | Bolsas no Brasil - Pós-Doutorado |
| Processo FAPESP: | 18/22214-6 - Rumo à convergência de tecnologias: de sensores e biossensores à visualização de informação e aprendizado de máquina para análise de dados em diagnóstico clínico |
| Beneficiário: | Osvaldo Novais de Oliveira Junior |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |