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

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 microfluidi...

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Autores principales: O’Sullivan, Shane, Ali, Zulfiqur, Jiang, Xiaoyi, Abdolvand, Reza, Ünlü, M Selim, Plácido da Silva, Hugo, Baca, Justin T., Kim, Brian, Scott, Simon, Sajid, Mohammed Imran, Moradian, Sina, Mansoorzare, Hakhamanesh, Holzinger, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515310/
https://www.ncbi.nlm.nih.gov/pubmed/31018573
http://dx.doi.org/10.3390/s19081917
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author O’Sullivan, Shane
Ali, Zulfiqur
Jiang, Xiaoyi
Abdolvand, Reza
Ünlü, M Selim
Plácido da Silva, Hugo
Baca, Justin T.
Kim, Brian
Scott, Simon
Sajid, Mohammed Imran
Moradian, Sina
Mansoorzare, Hakhamanesh
Holzinger, Andreas
author_facet O’Sullivan, Shane
Ali, Zulfiqur
Jiang, Xiaoyi
Abdolvand, Reza
Ünlü, M Selim
Plácido da Silva, Hugo
Baca, Justin T.
Kim, Brian
Scott, Simon
Sajid, Mohammed Imran
Moradian, Sina
Mansoorzare, Hakhamanesh
Holzinger, Andreas
author_sort O’Sullivan, Shane
collection PubMed
description 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.
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spelling pubmed-65153102019-05-30 Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing O’Sullivan, Shane Ali, Zulfiqur Jiang, Xiaoyi Abdolvand, Reza Ünlü, M Selim Plácido da Silva, Hugo Baca, Justin T. Kim, Brian Scott, Simon Sajid, Mohammed Imran Moradian, Sina Mansoorzare, Hakhamanesh Holzinger, Andreas Sensors (Basel) Article 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. MDPI 2019-04-23 /pmc/articles/PMC6515310/ /pubmed/31018573 http://dx.doi.org/10.3390/s19081917 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
O’Sullivan, Shane
Ali, Zulfiqur
Jiang, Xiaoyi
Abdolvand, Reza
Ünlü, M Selim
Plácido da Silva, Hugo
Baca, Justin T.
Kim, Brian
Scott, Simon
Sajid, Mohammed Imran
Moradian, Sina
Mansoorzare, Hakhamanesh
Holzinger, Andreas
Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing
title Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing
title_full Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing
title_fullStr Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing
title_full_unstemmed Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing
title_short Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing
title_sort developments in transduction, connectivity and ai/machine learning for point-of-care testing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6515310/
https://www.ncbi.nlm.nih.gov/pubmed/31018573
http://dx.doi.org/10.3390/s19081917
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