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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
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 |
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