Cargando…
Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19
OBJECTIVES: To develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19. METHODS: We included 424 patients with non-severe COVID-19 on admission from January 17, 2020, to February 17, 2020, in the primary cohort of this retrospective...
Autores principales: | Feng, Zhichao, Shen, Hui, Gao, Kai, Su, Jianpo, Yao, Shanhu, Liu, Qin, Yan, Zhimin, Duan, Junhong, Yi, Dali, Zhao, Huafei, Li, Huiling, Yu, Qizhi, Zhou, Wenming, Mao, Xiaowen, Ouyang, Xin, Mei, Ji, Zeng, Qiuhua, Williams, Lindy, Ma, Xiaoqian, Rong, Pengfei, Hu, Dewen, Wang, Wei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046645/ https://www.ncbi.nlm.nih.gov/pubmed/33856514 http://dx.doi.org/10.1007/s00330-021-07957-z |
Ejemplares similares
-
Commercial AI solutions in detecting COVID-19 pneumonia in chest CT: not yet ready for clinical implementation?
por: Jungmann, Florian, et al.
Publicado: (2021) -
Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation
por: Baltruschat, Ivo, et al.
Publicado: (2020) -
Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients
por: Mushtaq, Junaid, et al.
Publicado: (2020) -
Is the generalizability of a developed artificial intelligence algorithm for COVID-19 on chest CT sufficient for clinical use? Results from the International Consortium for COVID-19 Imaging AI (ICOVAI)
por: Topff, Laurens, et al.
Publicado: (2023) -
Artificial Intelligence–assisted chest X-ray assessment scheme for COVID-19
por: Rangarajan, Krithika, et al.
Publicado: (2021)