Cargando…
Understanding transfer learning for chest radiograph clinical report generation with modified transformer architectures
The image captioning task is increasingly prevalent in artificial intelligence applications for medicine. One important application is clinical report generation from chest radiographs. The clinical writing of unstructured reports is time consuming and error-prone. An automated system would improve...
Autores principales: | Vendrow, Edward, Schonfeld, Ethan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10372225/ https://www.ncbi.nlm.nih.gov/pubmed/37519756 http://dx.doi.org/10.1016/j.heliyon.2023.e17968 |
Ejemplares similares
-
On the relation of gene essentiality to intron structure: a computational and deep learning approach
por: Schonfeld, Ethan, et al.
Publicado: (2021) -
Comparing different deep learning architectures for classification of chest radiographs
por: Bressem, Keno K., et al.
Publicado: (2020) -
Analyzing Transfer Learning of Vision Transformers for Interpreting Chest Radiography
por: Usman, Mohammad, et al.
Publicado: (2022) -
Exploring transfer learning in chest radiographic images within the interplay between COVID-19 and diabetes
por: Shoaib, Muhammad, et al.
Publicado: (2023) -
Imaging the Chest: The Chest Radiograph
por: Broder, Joshua
Publicado: (2011)