Cargando…
Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes
The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence approaches to these problems, including using deep lear...
Autores principales: | Ortiz, Anthony, Trivedi, Anusua, Desbiens, Jocelyn, Blazes, Marian, Robinson, Caleb, Gupta, Sunil, Dodhia, Rahul, Bhatraju, Pavan K., Liles, W. Conrad, Lee, Aaron, Ferres, Juan M. Lavista |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810911/ https://www.ncbi.nlm.nih.gov/pubmed/35110593 http://dx.doi.org/10.1038/s41598-022-05532-0 |
Ejemplares similares
-
Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
por: Robinson, Caleb, et al.
Publicado: (2021) -
Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
por: Trivedi, Anusua, et al.
Publicado: (2022) -
Machine learning-based derivation and external validation of a tool to predict death and development of organ failure in hospitalized patients with COVID-19
por: Xu, Yixi, et al.
Publicado: (2022) -
Machine Learning-based Derivation and External Validation of a Tool to Predict Death and Development of Organ Failure in Hospitalized Patients with COVID-19
por: Xu, Yixi, et al.
Publicado: (2021) -
Democratizing Protein Language Models with Parameter-Efficient Fine-Tuning
por: Sledzieski, Samuel, et al.
Publicado: (2023)