Toward an Intelligent Computing Solution for Endotracheal Obstruction Prediction in COVID-19 Patients in ICU

Autor:	Guillermo Pérez-Acosta, Francisco J. Suárez-Díaz, Pablo Fernández-López, José Blanco-López, Carmen Paz Suárez-Araujo, Juan L. Navarro-Mesa, Patricio García-Báez
Rok vydání:	2021
Předmět:	medicine.medical_specialty 2019-20 coronavirus outbreak Respiratory illness Coronavirus disease 2019 (COVID-19) Intelligent computing business.industry Mortality rate respiratory system Icu admission Pandemic Emergency medicine Medicine Icu stay business
Zdroj:	Advances in Computational Intelligence ISBN: 9783030850296 IWANN (1)
DOI:	10.1007/978-3-030-85030-2_6
Popis:	Nowadays there is a world pandemic of a challenging respiratory illness, COVID-19. A large part of COVID-19 patients evolves to severe or fatal complications and require an ICU admission. COVID-19 mortality rate approaches 30% due to complications such as obstruction of the trachea and bronchi of patients during the ICU stay.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3c6ffe68f95d8561bdd8e9120a5d4db5 https://doi.org/10.1007/978-3-030-85030-2_6 Zobrazit plný text záznamu