Use data augmentation for a deep learning classification model with chest X-ray clinical imaging featuring coal workers' pneumoconiosis

PURPOSE: This paper aims to develop a successful deep learning model with data augmentation technique to discover the clinical uniqueness of chest X-ray imaging features of coal workers' pneumoconiosis (CWP). PATIENTS AND METHODS: We enrolled 149 CWP patients and 68 dust-exposure workers for a...

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Detalles Bibliográficos
Autores principales: Dong, Hantian, Zhu, Biaokai, Zhang, Xinri, Kong, Xiaomei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284687/
https://www.ncbi.nlm.nih.gov/pubmed/35840945
http://dx.doi.org/10.1186/s12890-022-02068-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284687/
https://www.ncbi.nlm.nih.gov/pubmed/35840945
http://dx.doi.org/10.1186/s12890-022-02068-x

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