Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images

It is still challenging to make accurate diagnosis of biliary atresia (BA) with sonographic gallbladder images particularly in rural areas without relevant expertise. Here, the authors develop a diagnostic deep learning model which favourable performance in comparison with human experts in multi-cen...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Wenying Zhou, Yang Yang, Cheng Yu, Juxian Liu, Xingxing Duan, Zongjie Weng, Dan Chen, Qianhong Liang, Qin Fang, Jiaojiao Zhou, Hao Ju, Zhenhua Luo, Weihao Guo, Xiaoyan Ma, Xiaoyan Xie, Ruixuan Wang, Luyao Zhou
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/97020172e8224071a01e636307ff2f72
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:97020172e8224071a01e636307ff2f72
record_format	dspace
spelling	oai:doaj.org-article:97020172e8224071a01e636307ff2f722021-12-02T13:30:08ZEnsembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images10.1038/s41467-021-21466-z2041-1723https://doaj.org/article/97020172e8224071a01e636307ff2f722021-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-21466-zhttps://doaj.org/toc/2041-1723It is still challenging to make accurate diagnosis of biliary atresia (BA) with sonographic gallbladder images particularly in rural areas without relevant expertise. Here, the authors develop a diagnostic deep learning model which favourable performance in comparison with human experts in multi-center external validation.Wenying ZhouYang YangCheng YuJuxian LiuXingxing DuanZongjie WengDan ChenQianhong LiangQin FangJiaojiao ZhouHao JuZhenhua LuoWeihao GuoXiaoyan MaXiaoyan XieRuixuan WangLuyao ZhouNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Wenying Zhou Yang Yang Cheng Yu Juxian Liu Xingxing Duan Zongjie Weng Dan Chen Qianhong Liang Qin Fang Jiaojiao Zhou Hao Ju Zhenhua Luo Weihao Guo Xiaoyan Ma Xiaoyan Xie Ruixuan Wang Luyao Zhou Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
description	It is still challenging to make accurate diagnosis of biliary atresia (BA) with sonographic gallbladder images particularly in rural areas without relevant expertise. Here, the authors develop a diagnostic deep learning model which favourable performance in comparison with human experts in multi-center external validation.
format	article
author	Wenying Zhou Yang Yang Cheng Yu Juxian Liu Xingxing Duan Zongjie Weng Dan Chen Qianhong Liang Qin Fang Jiaojiao Zhou Hao Ju Zhenhua Luo Weihao Guo Xiaoyan Ma Xiaoyan Xie Ruixuan Wang Luyao Zhou
author_facet	Wenying Zhou Yang Yang Cheng Yu Juxian Liu Xingxing Duan Zongjie Weng Dan Chen Qianhong Liang Qin Fang Jiaojiao Zhou Hao Ju Zhenhua Luo Weihao Guo Xiaoyan Ma Xiaoyan Xie Ruixuan Wang Luyao Zhou
author_sort	Wenying Zhou
title	Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
title_short	Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
title_full	Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
title_fullStr	Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
title_full_unstemmed	Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
title_sort	ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/97020172e8224071a01e636307ff2f72
work_keys_str_mv	AT wenyingzhou ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT yangyang ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT chengyu ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT juxianliu ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT xingxingduan ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT zongjieweng ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT danchen ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT qianhongliang ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT qinfang ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT jiaojiaozhou ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT haoju ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT zhenhualuo ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT weihaoguo ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT xiaoyanma ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT xiaoyanxie ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT ruixuanwang ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages AT luyaozhou ensembleddeeplearningmodeloutperformshumanexpertsindiagnosingbiliaryatresiafromsonographicgallbladderimages
_version_	1718392989984751616

Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images

Ejemplares similares