• Ricardo Luis Cobeñas, María de Vedia, Juan Florez, Daniela Jaramillo, Luciana Ferrari, and Ricardo Re.
• Departamento de Diagnóstico por Imágenes, Centro de Educación Medica e Investigaciones Clínicas Norberto Quirno (CEMIC), Buenos Aires, Argentina. Electronic address: ricardocobenas@gmail.com.
• Med Clin (Barc). 2023 Jan 20; 160 (2): 788178-81.

Introduction And ObjectivesTo evaluate the diagnostic performance of different artificial intelligence (AI) algorithms for the identification of pulmonary involvement by SARS-CoV-2 based on portable chest radiography (RX).Material And MethodsProspective observational study that included patients admitted for suspected COVID-19 infection in a university hospital between July and November 2020. The reference standard of pulmonary involvement by SARS-CoV-2 comprised a positive PCR test and low-tract respiratory symptoms.Results493 patients were included, 140 (28%) with positive PCR and 32 (7%) with SARS-CoV-2 pneumonia. The AI-B algorithm had the best diagnostic performance (areas under the ROC curve AI-B 0.73, vs. AI-A 0.51, vs. AI-C 0.57). Using a detection threshold greater than 55%, AI-B had greater diagnostic performance than the specialist [(area under the curve of 0.68 (95% CI 0.64-0.72), vs. 0.54 (95% CI 0.49-0.59)].ConclusionAI algorithms based on portable RX enabled a diagnostic performance comparable to human assessment for the detection of SARS-CoV-2 lung involvement.Copyright © 2022 Elsevier España, S.L.U. All rights reserved.

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