Lung ultrasound (LUS) imaging is playing an important role in the current pandemic, allowing the evaluation of patients affected by COVID-19 pneumonia. However, LUS is limited to the visual inspection of ultrasound data, which negatively affects the reproducibility and reliability of the findings. For these reasons, we were the first to propose a standardized imaging protocol and a scoring system, from which we developed the first artificial intelligence (AI) models able to evaluate LUS videos. Furthermore, we demonstrated prognostic value of our approach and its utility for patients' stratification. In this study, we report on the level of agreement between AI and LUS clinical experts (MD) on LUS data acquired from both COVID-19 patients and post-COVID-19 patients.

Automatically Scoring Lung Ultrasound Videos of COVID-19 and post-COVID-19 Patients / Mento, Federico; Di Sabatino, Antonio; Fiengo, Anna; Sabatini, Umberto; Macioce, Veronica Narvena; Tursi, Francesco; Sofia, Carmelo; Di Cienzo, Chiara; Smargiassi, Andrea; Inchingolo, Riccardo; Perrone, Tiziano; Demi, Libertario. - 2022-:(2022), pp. 1-4. ( 2022 IEEE International Ultrasonics Symposium, IUS 2022 Venice, Italy 10-13 October 2022) [10.1109/IUS54386.2022.9958500].

Automatically Scoring Lung Ultrasound Videos of COVID-19 and post-COVID-19 Patients

Mento, Federico;Demi, Libertario
2022-01-01

Abstract

Lung ultrasound (LUS) imaging is playing an important role in the current pandemic, allowing the evaluation of patients affected by COVID-19 pneumonia. However, LUS is limited to the visual inspection of ultrasound data, which negatively affects the reproducibility and reliability of the findings. For these reasons, we were the first to propose a standardized imaging protocol and a scoring system, from which we developed the first artificial intelligence (AI) models able to evaluate LUS videos. Furthermore, we demonstrated prognostic value of our approach and its utility for patients' stratification. In this study, we report on the level of agreement between AI and LUS clinical experts (MD) on LUS data acquired from both COVID-19 patients and post-COVID-19 patients.
2022
2022 IEEE International Ultrasonics Symposium (IUS)
Venezia, Italia
IEEE
978-1-6654-6657-8
Mento, Federico; Di Sabatino, Antonio; Fiengo, Anna; Sabatini, Umberto; Macioce, Veronica Narvena; Tursi, Francesco; Sofia, Carmelo; Di Cienzo, Chiara...espandi
Automatically Scoring Lung Ultrasound Videos of COVID-19 and post-COVID-19 Patients / Mento, Federico; Di Sabatino, Antonio; Fiengo, Anna; Sabatini, Umberto; Macioce, Veronica Narvena; Tursi, Francesco; Sofia, Carmelo; Di Cienzo, Chiara; Smargiassi, Andrea; Inchingolo, Riccardo; Perrone, Tiziano; Demi, Libertario. - 2022-:(2022), pp. 1-4. ( 2022 IEEE International Ultrasonics Symposium, IUS 2022 Venice, Italy 10-13 October 2022) [10.1109/IUS54386.2022.9958500].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/361286
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