Utilizing Deep Learning Algorithms for Signal Processing in Electrochemical Biosensors: From Data Augmentation to Detection and Quantification of Chemicals of Interest

Nanomaterial-based aptasensors serve as useful instruments for detecting small biological entities. This work utilizes data gathered from three electrochemical aptamer-based sensors varying in receptors, analytes of interest, and lengths of signals. Our ultimate objective was the automatic detection...

Descripció completa

Dades bibliogràfiques

Autors principals:	Fatemeh Esmaeili, Erica Cassie, Hong Phan T. Nguyen, Natalie O. V. Plank, Charles P. Unsworth, Alan Wang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2023-11-01
Col·lecció:	Bioengineering
Matèries:	data augmentation conditional variational auto-encoder (CVAE) signal extrapolation convolutional neural network (CNN) convolutional long short-term memory (ConvLSTM) long short-term memory (LSTM)
Accés en línia:	https://www.mdpi.com/2306-5354/10/12/1348
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!