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. 2022 Jun 12;12(6):e059110. doi: 10.1136/bmjopen-2021-059110

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© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Logistic regression-based machine learning model to detect the presence of COVID-19-related lung lesions. The patients were invited to participate in the study 6 months after COVID-19-positive RT-PCR at hospital admission. The modified Medical Research Council (mMRC) dyspnoea scale, oximetry (SpO₂), spirometry (forced vital capacity (FVC)) and the five radiographic scores obtained during DL-based classification of chest X-ray (pCXR) were used as input data, and the presence of lung lesions due to COVID-19 was used as output data. AI, artificial intelligence.