Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review.
Irkham IrkhamAbdullahi Umar IbrahimChidi Wilson NwekwoFadi Al-TurjmanYeni Wahyuni HartatiPublished in: Sensors (Basel, Switzerland) (2022)
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 includes 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 two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.
Keyphrases
- artificial intelligence
- coronavirus disease
- sars cov
- deep learning
- label free
- machine learning
- real time pcr
- loop mediated isothermal amplification
- big data
- respiratory syndrome coronavirus
- healthcare
- crispr cas
- public health
- health information
- dna methylation
- social media
- minimally invasive
- gene expression
- genome editing