Irkham, I.; Ibrahim, A.U.; Nwekwo, C.W.; Al-Turjman, F.; Hartati, Y.W. Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review. Sensors2023, 23, 426.
Irkham, I.; Ibrahim, A.U.; Nwekwo, C.W.; Al-Turjman, F.; Hartati, Y.W. Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review. Sensors 2023, 23, 426.
Irkham, I.; Ibrahim, A.U.; Nwekwo, C.W.; Al-Turjman, F.; Hartati, Y.W. Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review. Sensors2023, 23, 426.
Irkham, I.; Ibrahim, A.U.; Nwekwo, C.W.; Al-Turjman, F.; Hartati, Y.W. Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review. Sensors 2023, 23, 426.
Abstract
Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease. Technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which include RT-PCR, antigen-antibody and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include Deep Learning and Transfer learning approach. The review also provide comparison between these 2 emerging technologies and open research issues for the development of smart-IoMT-enable platform for the detection of COVID-19.
Keywords
Biosensors; COVID-19; Artificial Intelligence; Computer-aided Detection (CAD) Internet of Medical Things (IoMT).
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
