Recent Advances in Machine Learning for Electrochemical, Optical, and Gas Sensors

Abstract

Machine learning is increasingly used in the analysis of distinct types of data for clinical diagnosis and monitoring the environment, particularly because of the large amounts of data generated in sensing and biosensing methods. In this chapter, we discuss the usage of machine learning for electrochemical sensors, with emphasis on colorimetric principles of detection.