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, Sina Moradian, Mohammed Imran Sajid, Hakhamanesh Mansoorzare, Andreas Holzinger

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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.
Original languageEnglish
Article number1917
Number of pages31
JournalSensors
Volume19
Issue number8
DOIs
Publication statusPublished - 23 Apr 2019

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    O'Sullivan, S., Ali, Z., Jiang, X., Abdolvand, R., Ünlü, M. S., Plácido da Silva, H., Baca, J. T., Kim, B., Scott, S., Moradian, S., Sajid, M. I., Mansoorzare, H., & Holzinger, A. (2019). Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing. Sensors, 19(8), [1917]. https://doi.org/10.3390/s19081917