Artificial intelligence-based detection of aortic stenosis from chest radiographs

AIMS: We aimed to develop models to detect aortic stenosis (AS) from chest radiographs—one of the most basic imaging tests—with artificial intelligence. METHODS AND RESULTS: We used 10 433 retrospectively collected digital chest radiographs from 5638 patients to train, validate, and test three deep...

Descripción completa

Detalles Bibliográficos
Autores principales: Ueda, Daiju, Yamamoto, Akira, Ehara, Shoichi, Iwata, Shinichi, Abo, Koji, Walston, Shannon L, Matsumoto, Toshimasa, Shimazaki, Akitoshi, Yoshiyama, Minoru, Miki, Yukio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707887/
https://www.ncbi.nlm.nih.gov/pubmed/36713993
http://dx.doi.org/10.1093/ehjdh/ztab102

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707887/
https://www.ncbi.nlm.nih.gov/pubmed/36713993
http://dx.doi.org/10.1093/ehjdh/ztab102

Ejemplares similares