Santino Nanini on Muck Rack

Santino Nanini

As seen in: MDPI
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Articles

Machine and Deep Learning Models for Hypoxemia Severity Triage in CBRNE Emergencies

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By Santino Nanini, Mariem Abid, Yassir Mamouni, Arnaud Wiedemann
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Development and Comparative Analysis of Machine Learning Models for Hypoxemia Severity Triage in CBRNE Emergency Scenarios Using Physiological and Demographic Data from Medical-Grade Devices

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By Arnaud Wiedemann, Santino Nanini, Mariem Abid, Yassir Mamouni
| preprints.org
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 2 November 2024 / Approved: 4 November 2024 / Online: 4 November 2024 (09:30:06 CET) Nanini, S.; Abid, M.; Mamouni, Y.; Wiedemann, A.; Jouvet, P.; Bourassa, S. Development and Comparative Analysis of Machine Learning Models for Hypoxemia Severity Triage in CBRNE Emergency Scenarios Using Physiological and Demographic Data from Medical-Grade Devices. Preprints 2024, 2024110168.
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