Novel Diagnostic Approach for Acute Pharyngitis: Combining Machine Learning With Thermal Imaging

Abstract

We evaluated the effect of infrared thermography (IRT) on the clinical assessment of bacterial and viral pharyngitis and its impact on the predictive value of the McIsaac score algorithm for streptococcal pharyngitis in children. We also investigated if IRT could distinguish between bacterial and viral pharyngitis. The study included children aged 2–17 years presenting with sore throat and fever over 38°C from November 1, 2021, to April 30, 2022. Of the 76 assessed children, 16 were excluded due to missing data or technical issues, leaving 60 children (32 males, 28 females) divided into three groups: Group A with streptococcal pharyngitis (N = 30), viral pharyngitis (N = 16), and healthy controls (N = 14). McIsaac score and IRT imaging showed a 90% positive predictive value for streptococcal pharyngitis. While IRT alone could not distinguish between bacterial and viral infections, it significantly increased the predictive value when combined with the McIsaac score.