Biosensing has recently entered a new phase by introducing and applying concepts such as Important Health, Internet of Things (IoT) and Big Data. The development of intelligent biosensors aims to break the limitations of centralized, reactive healthcare by providing individuals with information about their physical dynamics; however, complex causality creates extreme difficulties in outcome analysis. Integrating artificial intelligence (AI) approaches, including pattern analysis and classification algorithms, into biosensors can bridge the gap between data collection and analysis and improve diagnostic and treatment accuracy.

This webinar aims to present the latest developments in artificial intelligence biosensors. It also highlights possible future AI biosensors and advanced programming capabilities, including AI diagnostics, big data processing, and self-optimization. Such AI biosensors are hybrid techniques of wireless biosensor technology and advanced machine learning algorithms, showing promise in realizing continuous healthcare monitoring and cloud-connected point-of-care (POC) diagnostics.