The Covid-19 Decision Support System (C19DSS) – A Mobile App

Vittorini, Pierpaolo; Casano, Nicolò; Sinatti, Gaia; Santini, Silvano Junior; Balsano, Clara

doi:10.1007/978-3-031-17024-9_3

Cited by 1 publication

(2 citation statements)

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“…Physicians reported that the application was easy ed intuitive to use; the process of data entry and classification did not hamper the normal ED work routine. More details on the system, its architecture and on the usability results can be found in a further papers of our research group [ 19 ].…”

Section: Resultsmentioning

confidence: 99%

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Application of machine learning approach in emergency department to support clinical decision making for SARS-CoV-2 infected patients

Casano

Santini

Vittorini

et al. 2023

Journal of Integrative Bioinformatics

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To support physicians in clinical decision process on patients affected by Coronavirus Disease 2019 (COVID-19) in areas with a low vaccination rate, we devised and evaluated the performances of several machine learning (ML) classifiers fed with readily available clinical and laboratory data. Our observational retrospective study collected data from a cohort of 779 COVID-19 patients presenting to three hospitals of the Lazio-Abruzzo area (Italy). Based on a different selection of clinical and respiratory (ROX index and PaO2/FiO2 ratio) variables, we devised an AI-driven tool to predict safe discharge from ED, disease severity and mortality during hospitalization. To predict safe discharge our best classifier is an RF integrated with ROX index that reached AUC of 0.96. To predict disease severity the best classifier was an RF integrated with ROX index that reached an AUC of 0.91. For mortality prediction the best classifier was an RF integrated with ROX index, that reached an AUC of 0.91. The results obtained thanks to our algorithms are consistent with the scientific literature an accomplish significant performances to forecast safe discharge from ED and severe clinical course of COVID-19.

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Section: Resultsmentioning

confidence: 99%

“…The work presented in this paper is part of a larger research project whose aim was to design, develop and test a decision support system, called C19DSS (COVID-19 Decision Support System), based on ML predictors, that should assist physicians in clinical decision making [ 19 ].…”

Section: Introductionmentioning

confidence: 99%