Investigating public behavior with artificial intelligence-assisted detection of face mask wearing during the COVID-19 pandemic.

ABSTRACT:

Objectives

Face masks are low-cost, but effective in preventing transmission of COVID-19. To visualize public's practice of protection during the outbreak, we reported the rate of face mask wearing using artificial intelligence-assisted face mask detector, AiMASK.

Methods

After validation, AiMASK collected data from 32 districts in Bangkok. We analyzed the association between factors affecting the unprotected group (incorrect or non-mask wearing) using univariate logistic regression analysis.

Results

AiMASK was validated before data collection with accuracy of 97.83% and 91% during internal and external validation, respectively. AiMASK detected a total of 1,124,524 people. The unprotected group consisted of 2.06% of incorrect mask-wearing group and 1.96% of non-mask w

SUBMITTER: Seresirikachorn K 

PROVIDER: S-EPMC10089330 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature