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

Autor: 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
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Sensors, Vol 19, Iss 8, p 1917 (2019)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s19081917
Popis: 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.
Databáze: Directory of Open Access Journals
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