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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-6515310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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