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公开(公告)号:US20210035689A1
公开(公告)日:2021-02-04
申请号:US16967087
申请日:2018-04-17
发明人: Xiaoqing Liu , Jiaxu Hong , Yong Ni , Shuangshuang Li , Lili Wang , Wei He , Youwen Guo , Yuxuan Liu , Yong Liu , Wei Wang , Ruiqi Xu , Jingyi Cheng , Lijia Tian , Wenbin Chen , Xun Xu
摘要: The present disclosure proposes a modeling method and apparatus for diagnosing an ophthalmic disease based on artificial intelligence, and a storage medium. The modeling method includes: establishing a data collection of ophthalmic images and a data collection of non-image ophthalmic disease diagnosis questionnaires; training a first neural network model by employing the data collection of the ophthalmic images to obtain a first classification model; training a second classification model by employing the data collection of non-image ophthalmic disease diagnosis questionnaires; and merging the first classification model and the second classification model to obtain a target classification network model, in which, a test result outputted by the target classification network model is used as a diagnosis result of the ophthalmic disease.
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公开(公告)号:US11636340B2
公开(公告)日:2023-04-25
申请号:US16967087
申请日:2018-04-17
发明人: Xiaoqing Liu , Jiaxu Hong , Yong Ni , Shuangshuang Li , Lili Wang , Wei He , Youwen Guo , Yuxuan Liu , Yong Liu , Wei Wang , Ruiqi Xu , Jingyi Cheng , Lijia Tian , Wenbin Chen , Xun Xu
IPC分类号: G06N3/08 , G16H50/20 , G16H10/20 , A61B3/12 , A61B3/14 , G06T7/00 , G06F18/214 , G06F18/21 , G06V10/764 , G06V10/80 , G06V10/82 , G06V20/69
摘要: The present disclosure proposes a modeling method and apparatus for diagnosing an ophthalmic disease based on artificial intelligence, and a storage medium. The modeling method includes: establishing a data collection of ophthalmic images and a data collection of non-image ophthalmic disease diagnosis questionnaires; training a first neural network model by employing the data collection of the ophthalmic images to obtain a first classification model; training a second classification model by employing the data collection of non-image ophthalmic disease diagnosis questionnaires; and merging the first classification model and the second classification model to obtain a target classification network model, in which, a test result outputted by the target classification network model is used as a diagnosis result of the ophthalmic disease.
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