Investigating the use of a two-stage attention-aware convolutional neural network for the automated diagnosis of otitis media from tympanic membrane images: a prediction model development and validation study

OBJECTIVES: This study investigated the usefulness and performance of a two-stage attention-aware convolutional neural network (CNN) for the automated diagnosis of otitis media from tympanic membrane (TM) images. DESIGN: A classification model development and validation study in ears with otitis med...

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Detalles Bibliográficos
Autores principales: Cai, Yuexin, Yu, Jin-Gang, Chen, Yuebo, Liu, Chu, Xiao, Lichao, M Grais, Emad, Zhao, Fei, Lan, Liping, Zeng, Shengxin, Zeng, Junbo, Wu, Minjian, Su, Yuejia, Li, Yuanqing, Zheng, Yiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Ear, Nose and Throat/Otolaryngology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7825258/
https://www.ncbi.nlm.nih.gov/pubmed/33478963
http://dx.doi.org/10.1136/bmjopen-2020-041139

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7825258/
https://www.ncbi.nlm.nih.gov/pubmed/33478963
http://dx.doi.org/10.1136/bmjopen-2020-041139

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