Overview in Machine-Learning-Assisted Sensing Techniques for Monitoring COVID-19
Viruses suddenly emerging from obscurity or anonymity affect our quality of life and increase incidence rate and mortality. A typical example is the global coronavirus disease 2019 (COVID-19) pandemic. Although severe acute respiratory syndrome coronavirus 2, known as the pathogen of COVID-19 has been significantly eliminated, its monitoring is still crucial, as the infectious disease may break out again. Therefore, it is necessary to develop simple and effective tools for monitoring COVID-19 and other diseases. Here, we summarize the progress of machine-learning-based biosensors in the monitoring and management of COVID-19. This article mainly includes three sections: machine learning algorithms, machine-learning-assisted biosensors, and challenges and future perspectives. We believe that this work is valuable for developing artificial-intelligence-based innovative analytical devices for healthcare monitoring and management of COVID-19 and other infectious diseases.
Authors
- Ming La
- Yan Feng
Institutions
- Pingdingshan University (CN)
Publication Details
- Journal
- Micromachines
- Published
- 2026-02-25
- DOI
- https://doi.org/10.3390/mi17030283
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00