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Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Lippincott Williams & Wilkins
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9555852/ https://www.ncbi.nlm.nih.gov/pubmed/36206146 http://dx.doi.org/10.1097/CIN.0000000000000943 |
| _version_ | 1784806944373997568 |
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| author | Alderden, Jenny Kennerly, Susan M. Wilson, Andrew Dimas, Jonathan McFarland, Casey Yap, David Y. Zhao, Lucy Yap, Tracey L. |
| author_facet | Alderden, Jenny Kennerly, Susan M. Wilson, Andrew Dimas, Jonathan McFarland, Casey Yap, David Y. Zhao, Lucy Yap, Tracey L. |
| author_sort | Alderden, Jenny |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-9555852 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Lippincott Williams & Wilkins |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-95558522022-10-14 Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients Alderden, Jenny Kennerly, Susan M. Wilson, Andrew Dimas, Jonathan McFarland, Casey Yap, David Y. Zhao, Lucy Yap, Tracey L. Comput Inform Nurs DEPARTMENTS: CIN Plus Lippincott Williams & Wilkins 2022-10-05 /pmc/articles/PMC9555852/ /pubmed/36206146 http://dx.doi.org/10.1097/CIN.0000000000000943 Text en Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved. This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections. |
| spellingShingle | DEPARTMENTS: CIN Plus Alderden, Jenny Kennerly, Susan M. Wilson, Andrew Dimas, Jonathan McFarland, Casey Yap, David Y. Zhao, Lucy Yap, Tracey L. Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients |
| title | Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients |
| title_full | Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients |
| title_fullStr | Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients |
| title_full_unstemmed | Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients |
| title_short | Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19–Positive Critical Care Patients |
| title_sort | explainable artificial intelligence for predicting hospital-acquired pressure injuries in covid-19–positive critical care patients |
| topic | DEPARTMENTS: CIN Plus |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9555852/ https://www.ncbi.nlm.nih.gov/pubmed/36206146 http://dx.doi.org/10.1097/CIN.0000000000000943 |
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