Cargando…
Intubation and mortality prediction in hospitalized COVID-19 patients using a combination of convolutional neural network-based scoring of chest radiographs and clinical data
OBJECTIVE: To predict short-term outcomes in hospitalized COVID-19 patients using a model incorporating clinical variables with automated convolutional neural network (CNN) chest radiograph analysis. METHODS: A retrospective single center study was performed on patients consecutively admitted with C...
Autores principales: | O'Shea, Aileen, Li, Matthew D, Mercaldo, Nathaniel D, Balthazar, Patricia, Som, Avik, Yeung, Tristan, Succi, Marc D, Little, Brent P, Kalpathy-Cramer, Jayashree, Lee, Susanna I |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The British Institute of Radiology.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459864/ https://www.ncbi.nlm.nih.gov/pubmed/36105420 http://dx.doi.org/10.1259/bjro.20210062 |
Ejemplares similares
-
Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs using Convolutional Siamese Neural Networks
por: Li, Matthew D., et al.
Publicado: (2020) -
Multi-Radiologist User Study for Artificial Intelligence-Guided Grading of COVID-19 Lung Disease Severity on Chest Radiographs
por: Li, Matthew D., et al.
Publicado: (2021) -
Rate of True-Positive Findings of COVID-19 Typical Appearance at
Chest CT per RSNA Consensus Guidelines in an Increasingly Vaccinated
Population
por: Polyakov, Nicole J., et al.
Publicado: (2022) -
Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19
por: Li, Matthew D., et al.
Publicado: (2022) -
Imaging Volume Trends and Recovery During the COVID-19 Pandemic: A Comparative Analysis Between a Large Urban Academic Hospital and Its Affiliated Imaging Centers
por: Lang, Min, et al.
Publicado: (2020)