Year: 2026
Type: article
Abstract: To investigate the potential application of existing artificial intelligence (AI) software in diagnosing COVID-19 (coronavirus disease 2019) and other pneumonia-related radiographic findings with the unprecedented challenge by COVID-19 pandemic, leveraging pre-trained commercial AI software originally designed for detecting pulmonary nodules in chest radiographs, we assessed its performance using public dataset comprising chest radiographs collected during the early stages of pandemic. The software demonstrated promising results, achieving a sensitivity of 86.83% and a specificity of 59.59% in detecting pneumonia features, including those caused by COVID-19. Considering only posterior-anterior (PA) radiographs, AI software exhibited improved performance, with sensitivity 89.16% and specificity 67.41%. The findings suggest the AI CAD software could serve as a triage for initial screening of infectious pulmonary diseases, especially in regions with limited access to advanced medical resources. This study underscores the importance of promptly adapting existing AI CAD to address urgent healthcare needs during infectious disease outbreaks.
Source: Scientific Reports
Author: Young Beom Kim
Institution: Pyeongtaek University
Language: English
Topic: COVID-19 diagnosis using AI
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7118521630