COVID-19-related pneumonia is typically diagnosed using chest x-ray or computed tomography images. However, these techniques can only be used in hospitals. In contrast, thermal cameras are portable, inexpensive devices that can be connected to smartphones. Thus, they can be used to detect and monitor medical conditions outside hospitals. Herein, a smartphone-based application using thermal images of a human back was developed for COVID-19 detection. Image analysis using a deep learning algorithm revealed a sensitivity and specificity of 88.7% and 92.3%, respectively. The findings support the future use of noninvasive thermal imaging in primary screening for COVID-19 and associated pneumonia.

Download full-text PDF

Source
http://dx.doi.org/10.1002/jbio.202300486DOI Listing

Publication Analysis

Top Keywords

covid-19 associated
8
associated pneumonia
8
thermal imaging
8
learning algorithm
8
smartphone-based detection
4
detection covid-19
4
thermal
4
pneumonia thermal
4
imaging transfer
4
transfer learning
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!