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Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing

Authors :
Mohammed Imran Sajid
M. Selim Ünlü
Simon M. Scott
Xiaoyi Jiang
Justin T. Baca
Shane O'Sullivan
Sina Moradian
Reza Abdolvand
Hakhamanesh Mansoorzare
Zulfiqur Ali
Andreas Holzinger
Hugo Silva
Brian N. Kim
Source :
Sensors (Basel, Switzerland), Sensors, Vol 19, Iss 8, p 1917 (2019), Sensors, Volume 19, Issue 8
Publication Year :
2019
Publisher :
MDPI, 2019.

Abstract

We review some emerging trends in transduction, connectivity and data analytics for Point-of-Care Testing (POCT) of infectious and non-communicable diseases. The patient need for POCT is described along with developments in portable diagnostics, specifically in respect of Lab-on-chip and microfluidic systems. We describe some novel electrochemical and photonic systems and the use of mobile phones in terms of hardware components and device connectivity for POCT. Developments in data analytics that are applicable for POCT are described with an overview of data structures and recent AI/Machine learning trends. The most important methodologies of machine learning, including deep learning methods, are summarised. The potential value of trends within POCT systems for clinical diagnostics within Lower Middle Income Countries (LMICs) and the Least Developed Countries (LDCs) are highlighted.

Details

Language :
English
ISSN :
14248220
Volume :
19
Issue :
8
Database :
OpenAIRE
Journal :
Sensors (Basel, Switzerland)
Accession number :
edsair.doi.dedup.....46127029db1e87fabbde96fe21792f16