%0 Journal Article
%@ 2561-326X
%I JMIR Publications
%V 8
%N 
%P e46817
%T Comparison of the Discrimination Performance of AI Scoring and the Brixia Score in Predicting COVID-19 Severity on Chest X-Ray Imaging: Diagnostic Accuracy Study
%A Tenda,Eric Daniel
%A Yunus,Reyhan Eddy
%A Zulkarnaen,Benny
%A Yugo,Muhammad Reynalzi
%A Pitoyo,Ceva Wicaksono
%A Asaf,Moses Mazmur
%A Islamiyati,Tiara Nur
%A Pujitresnani,Arierta
%A Setiadharma,Andry
%A Henrina,Joshua
%A Rumende,Cleopas Martin
%A Wulani,Vally
%A Harimurti,Kuntjoro
%A Lydia,Aida
%A Shatri,Hamzah
%A Soewondo,Pradana
%A Yusuf,Prasandhya Astagiri
%+ Department of Medical Physiology and Biophysics/ Medical Technology Cluster IMERI, Faculty of Medicine, Universitas Indonesia, Jalan Salemba Raya No.6, Jakarta, 10430, Indonesia, 62 812 8459 4272, prasandhya.a.yusuf@ui.ac.id
%K artificial intelligence
%K Brixia
%K chest x-ray
%K COVID-19
%K CAD4COVID
%K pneumonia
%K radiograph
%K artificial intelligence scoring system
%K AI scoring system
%K prediction
%K disease severity
%D 2024
%7 7.3.2024
%9 Original Paper
%J JMIR Form Res
%G English
%X Background: The artificial intelligence (AI) analysis of chest x-rays can increase the precision of binary COVID-19 diagnosis. However, it is unknown if AI-based chest x-rays can predict who will develop severe COVID-19, especially in low- and middle-income countries. Objective: The study aims to compare the performance of human radiologist Brixia scores versus 2 AI scoring systems in predicting the severity of COVID-19 pneumonia. Methods: We performed a cross-sectional study of 300 patients suspected with and with confirmed COVID-19 infection in Jakarta, Indonesia. A total of 2 AI scores were generated using CAD4COVID x-ray software. Results: The AI probability score had slightly lower discrimination (area under the curve [AUC] 0.787, 95% CI 0.722-0.852). The AI score for the affected lung area (AUC 0.857, 95% CI 0.809-0.905) was almost as good as the human Brixia score (AUC 0.863, 95% CI 0.818-0.908). Conclusions: The AI score for the affected lung area and the human radiologist Brixia score had similar and good discrimination performance in predicting COVID-19 severity. Our study demonstrated that using AI-based diagnostic tools is possible, even in low-resource settings. However, before it is widely adopted in daily practice, more studies with a larger scale and that are prospective in nature are needed to confirm our findings. 
%M 38451633
%R 10.2196/46817
%U https://formative.jmir.org/2024/1/e46817
%U https://doi.org/10.2196/46817
%U http://www.ncbi.nlm.nih.gov/pubmed/38451633