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公开(公告)号：US11842268B2
公开(公告)日：2023-12-12
申请号：US16648719
申请日：2018-09-10
发明人： Dimitrios Mavroeidis , Monique Hendriks , Pieter Christiaan Vos , Sergio Consoli , Jacek Lukasz Kustra , Johan Janssen , Ralf Dieter Hoffmann
IPC分类号： G06N3/08 , G16H10/60 , G16H50/70 , G06N20/00 , G06F17/18 , G06F18/214 , G06F18/23213
CPC分类号： G06N3/08 , G06F17/18 , G06F18/214 , G06F18/23213 , G06N20/00 , G16H10/60 , G16H50/70
摘要： The invention provides a method for evaluating a set of input data, the input data comprising at least one of: clinical data of a subject; genomic data of a subject; clinical data of a plurality of subjects; and genomic data of a plurality of subjects, using a deep learning algorithm. The method includes obtaining a set of input data, wherein the set of input data comprises raw data arranged into a plurality of data clusters and tuning the deep learning algorithm based on the plurality of data clusters. The deep learning algorithm comprises: an input layer; an output layer; and a plurality of hidden layers. The method further includes performing statistical clustering on the raw data using the deep learning algorithm, thereby generating statistical clusters and obtaining a marker from each statistical cluster. Finally, the set of input data is evaluated based on the markers to derive data of medical relevance in respect of the subject or subjects.
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公开(公告)号：US20200251224A1
公开(公告)日：2020-08-06
申请号：US16648719
申请日：2018-09-10
发明人： Dimitrios Mavroeidis , Monique Hendriks , Pieter Christiaan Vos , Sergio Consoli , Jacek Lukasz Kustra , Johan Janssen , Ralf Dieter Hoffmann
摘要： The invention provides a method for evaluating a set of input data, the input data comprising at least one of: clinical data of a subject; genomic data of a subject; clinical data of a plurality of subjects; and genomic data of a plurality of subjects, using a deep learning algorithm. The method includes obtaining a set of input data, wherein the set of input data comprises raw data arranged into a plurality of data clusters and tuning the deep learning algorithm based on the plurality of data clusters. The deep learning algorithm comprises: an input layer; an output layer; and a plurality of hidden layers. The method further includes performing stabstical clustering on the raw data using the deep learning algorithm, thereby generating statistical clusters and obtaining a marker from each statistical cluster. Finally, the set of input data is evaluated based on the markers to derive data of medical relevance in respect of the subject or subjects.
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