Development and Validation of a Deep Learning–Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs

IMPORTANCE: Interpretation of chest radiographs is a challenging task prone to errors, requiring expert readers. An automated system that can accurately classify chest radiographs may help streamline the clinical workflow. OBJECTIVES: To develop a deep learning–based algorithm that can classify norm...

Descripción completa

Detalles Bibliográficos
Autores principales: Hwang, Eui Jin, Park, Sunggyun, Jin, Kwang-Nam, Kim, Jung Im, Choi, So Young, Lee, Jong Hyuk, Goo, Jin Mo, Aum, Jaehong, Yim, Jae-Joon, Cohen, Julien G., Ferretti, Gilbert R., Park, Chang Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2019
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6583308/
https://www.ncbi.nlm.nih.gov/pubmed/30901052
http://dx.doi.org/10.1001/jamanetworkopen.2019.1095

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6583308/
https://www.ncbi.nlm.nih.gov/pubmed/30901052
http://dx.doi.org/10.1001/jamanetworkopen.2019.1095

Ejemplares similares