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Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing
- Source :
- Sensors (Basel, Switzerland), Sensors, Vol 19, Iss 8, p 1917 (2019), Sensors, Volume 19, Issue 8
- Publication Year :
- 2019
- Publisher :
- MDPI, 2019.
-
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.
- Subjects :
- Transduction (machine learning)
Computer science
Point-of-care testing
photonics
microfluidics
02 engineering and technology
lcsh:Chemical technology
Machine learning
computer.software_genre
01 natural sciences
Biochemistry
Article
POCT
Analytical Chemistry
lcsh:TP1-1185
Electrical and Electronic Engineering
Instrumentation
mobile phone
business.industry
010401 analytical chemistry
deep learning
021001 nanoscience & nanotechnology
artificial intelligence
Atomic and Molecular Physics, and Optics
3. Good health
0104 chemical sciences
Mobile phone
Data analysis
Artificial intelligence
0210 nano-technology
business
computer
Subjects
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 19
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- Sensors (Basel, Switzerland)
- Accession number :
- edsair.doi.dedup.....46127029db1e87fabbde96fe21792f16