Zobrazeno 1 - 10
of 37
pro vyhledávání: '"anesthesia and intensive care"'
Publikováno v:
Applied Medical Informatics, Vol 45, Iss Suppl. S1, Pp S36-S36 (2023)
Background and Aim: The modern surgical environment is complex and has a high potential risk of medical errors. In this context, the attitudes of healthcare professionals regarding patient safety represent an important component of organizational saf
Externí odkaz:
https://doaj.org/article/9c43aed224ca47f9bbffe421130e1840
Publikováno v:
Romanian Journal of Population Studies. 16(1):95-120
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=1054618
Publikováno v:
Frontiers in Medicine, Vol 8 (2021)
Objective: Predicting prognosis of in-hospital patients is critical. However, it is challenging to accurately predict the life and death of certain patients at certain period. To determine whether machine learning algorithms could predict in-hospital
Externí odkaz:
https://doaj.org/article/0c88e0283ba045c0864b5ea0cbaa2793
Akademický článek
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Autor:
Matteo Villani, Valentina Lob, Anna Del Prete, Emmanuele Guerra, Elisabetta Chili, Elisabetta Bertellini
Publikováno v:
International Journal of Environmental Research and Public Health; Volume 19; Issue 19; Pages: 12645
Introduction: The study aims to describe the organization of one accredited school of Anesthesia and Intensive Care of University of Modena and Reggio Emilia, Italy. The analysis of the post-graduation period aims to measure the time-to-first job, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fd0a1c58d4622c43646ef57a42e02c2
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Autor:
Andrea Kazamer, Radu Ilinca, Anda Nitu, Ana-Maria Iuonuț, Serban-Ion Bubenek-Turconi, Gerald Sendlhofer, Maria Greabu, Iulia-Ioana Stanescu-Spinu, Daniela Miricescu, Ionela Ganea, Daniela Ionescu
Publikováno v:
Healthcare
Volume 11
Issue 3
Pages: 429
Volume 11
Issue 3
Pages: 429
Due to the nature of their activity, anesthesia and critical care have generally well-developed patient safety cultures, which are linked to a greater level of incident awareness and reporting during clinical activity. In order to determine the statu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fcb346309405854370e0a3b7f8590a0a
https://doi.org/10.3390/healthcare11030429
https://doi.org/10.3390/healthcare11030429
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
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Publikováno v:
Indian Journal of Critical Care Medicine : Peer-reviewed, Official Publication of Indian Society of Critical Care Medicine
Background: Ventilator-associated pneumonia (VAP) is one of the most common hospital-acquired infections among mechanically ventilated patients and the incidence rates are widely used as an index of quality of care given in an ICU. Since there is no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::553e7dfb113b3255f55acca6b5ab87fa
http://europepmc.org/articles/PMC7991760
http://europepmc.org/articles/PMC7991760
Publikováno v:
Frontiers in Medicine, Vol 8 (2021)
Frontiers in Medicine
Frontiers in Medicine
Objective: Predicting prognosis of in-hospital patients is critical. However, it is challenging to accurately predict the life and death of certain patients at certain period. To determine whether machine learning algorithms could predict in-hospital
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3bcc608cd0f23e5ac436d883dc870c6
https://resolver.caltech.edu/CaltechAUTHORS:20210505-082417501
https://resolver.caltech.edu/CaltechAUTHORS:20210505-082417501
