Overview in Machine-Learning-Assisted Sensing Techniques for Monitoring COVID-19

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Authors: Yan Feng, Ming La
Cited by: 2
References: 73

Abstract

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.

Fields of Study & Subjects

COVID-19 diagnosis using AI SARS-CoV-2 detection and testing COVID-19 Digital Contact Tracing

Publication details

Journal / source
Micromachines
Publisher
MDPI AG
Volume
17
Issue
3
Pages
283–283
Publication date
25 February 2026
Language
EN