Efficacy of a comprehensive binary classification model using a deep convolutional neural network for wireless capsule endoscopy

Efficacy of a comprehensive binary classification model using a deep convolutional neural network for wireless capsule endoscopy

Abstract The manual reading of capsule endoscopy (CE) videos in small bowel disease diagnosis is time-intensive. Algorithms introduced to automate this process are premature for real clinical applications, and multi-diagnosis using these methods has not been sufficiently validated. Therefore, we dev...

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Autores principales: Sang Hoon Kim, Youngbae Hwang, Dong Jun Oh, Ji Hyung Nam, Ki Bae Kim, Junseok Park, Hyun Joo Song, Yun Jeong Lim
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/c7ec7dda26254e068eb086a14b675a25
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