Developments in transduction, connectivity and AI/machine learning for point-of-care testing

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

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in einer FachzeitschriftArtikelBegutachtung

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.

Originalspracheenglisch
Aufsatznummer1917
FachzeitschriftSensors
Jahrgang19
Ausgabenummer8
DOIs
PublikationsstatusVeröffentlicht - 2 Apr. 2019

ASJC Scopus subject areas

  • Analytische Chemie
  • Biochemie
  • Atom- und Molekularphysik sowie Optik
  • Instrumentierung
  • Elektrotechnik und Elektronik

Fingerprint

Untersuchen Sie die Forschungsthemen von „Developments in transduction, connectivity and AI/machine learning for point-of-care testing“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren