COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data

OBJECTIVES: We aimed to develop deep learning models using longitudinal chest X-rays (CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive care unit (ICU). METHODS: Six hundred fifty-four patients (212 deceased, 442 alive, 5645 total CXRs) were identified ac...

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Detalles Bibliográficos
Autores principales: Cheng, Jianhong, Sollee, John, Hsieh, Celina, Yue, Hailin, Vandal, Nicholas, Shanahan, Justin, Choi, Ji Whae, Tran, Thi My Linh, Halsey, Kasey, Iheanacho, Franklin, Warren, James, Ahmed, Abdullah, Eickhoff, Carsten, Feldman, Michael, Mortani Barbosa, Eduardo, Kamel, Ihab, Lin, Cheng Ting, Yi, Thomas, Healey, Terrance, Zhang, Paul, Wu, Jing, Atalay, Michael, Bai, Harrison X., Jiao, Zhicheng, Wang, Jianxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Chest
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857913/
https://www.ncbi.nlm.nih.gov/pubmed/35184218
http://dx.doi.org/10.1007/s00330-022-08588-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857913/
https://www.ncbi.nlm.nih.gov/pubmed/35184218
http://dx.doi.org/10.1007/s00330-022-08588-8

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