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

Shane O’Sullivan; Zulfiqur Ali; Xiaoyi Jiang; Reza Abdolvand; M  Selim Ünlü; Hugo Plácido da Silva; Justin  T. Baca; Brian Kim; Simon Scott; Mohammed  Imran Sajid; Sina Moradian; Hakhamanesh Mansoorzare; Andreas Holzinger

doi:10.3390/s19081917

Sensors (Apr 2019)

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

Shane O’Sullivan,
Zulfiqur Ali,
Xiaoyi Jiang,
Reza Abdolvand,
M Selim Ünlü,
Hugo Plácido da Silva,
Justin T. Baca,
Brian Kim,
Simon Scott,
Mohammed Imran Sajid,
Sina Moradian,
Hakhamanesh Mansoorzare,
Andreas Holzinger

Affiliations

Shane O’Sullivan: Department of Pathology, Faculdade de Medicina, Universidade de São Paulo, São Paulo 05508-060, Brazil
Zulfiqur Ali: Healthcare Innovation Centre, Teesside University, Middlesbrough TS1 3BX, UK
Xiaoyi Jiang: Faculty of Mathematics and Computer Science, University Münster, 48149 Münster, Germany
Reza Abdolvand: Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA
M Selim Ünlü: Department of Electrical and Computer Engineering and Biomedical Engineering, Boston University, Boston, MA 02215, USA
Hugo Plácido da Silva: IT—Instituto de Telecomunicações, 1049-001 Lisbon, Portugal
Justin T. Baca: Department of Emergency Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA
Brian Kim: Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA
Simon Scott: Healthcare Innovation Centre, Teesside University, Middlesbrough TS1 3BX, UK
Mohammed Imran Sajid: Department of Upper GI Surgery, Wirral University Teaching Hospital, Wirral CH49 5PE, UK
Sina Moradian: Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA
Hakhamanesh Mansoorzare: Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA
Andreas Holzinger: Institute for interactive Systems and Data Science, Graz University of Technology, 8074 Graz, Austria

DOI: https://doi.org/10.3390/s19081917
Journal volume & issue: Vol. 19, no. 8
p. 1917

Abstract

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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.

Published in Sensors

ISSN: 1424-8220 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Chemical technology
Website: http://www.mdpi.com/journal/sensors

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