| Full text | |
| Author(s): |
Neto, Mario Popolin
[1, 2]
;
Soares, Andrey Coatrini
[3]
;
Oliveira Jr, Osvaldo N.
;
Paulovich, V, Fernando
Total Authors: 4
|
| Affiliation: | [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
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN; v. 94, n. 5, p. 1553-1562, MAY 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
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) | |
| FAPESP's process: | 18/18953-8 - Nanostructured films applied in microfluidic biosensors to mastitis detection |
| Grantee: | Andrey Coatrini Soares |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 18/22214-6 - Towards a convergence of technologies: from sensing and biosensing to information visualization and machine learning for data analysis in clinical diagnosis |
| Grantee: | Osvaldo Novais de Oliveira Junior |
| Support Opportunities: | Research Projects - Thematic Grants |