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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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Detalles Bibliográficos
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
Descripción
Sumario: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.