Risk Assessment of COVID-19 Cases in Emergency Departments and Clinics With the Use of Real-World Data and Artificial Intelligence: Observational Study | Zendy

Evangelos Logaras | Zendy; Antonis Billis | Zendy; Ilias Kyparissidis Kokkinidis | Zendy; Smaranda Nafsika Ketseridou | Zendy; Alexios Fourlis | Zendy; Aristotelis Tzotzis | Zendy; Κonstantinos Imprialos | Zendy; Michael Doumas | Zendy; Panagiotis D. Bamidis | Zendy

Open Access

Risk Assessment of COVID-19 Cases in Emergency Departments and Clinics With the Use of Real-World Data and Artificial Intelligence: Observational Study

Author(s) -

Evangelos Logaras,

Antonis Billis,

Ilias Kyparissidis Kokkinidis,

Smaranda Nafsika Ketseridou,

Alexios Fourlis,

Aristotelis Tzotzis,

Κonstantinos Imprialos,

Michael Doumas,

Panagiotis D. Bamidis

Publication year - 2022

Publication title -

jmir formative research

Language(s) - English

Resource type - Journals

ISSN - 2561-326X

DOI - 10.2196/36933

Subject(s) - medical emergency , wearable computer , observational study , random forest , intensive care unit , medicine , vital signs , emergency department , data collection , covid-19 , emergency medicine , computer science , artificial intelligence , intensive care medicine , disease , nursing , statistics , surgery , mathematics , pathology , infectious disease (medical specialty) , embedded system

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