公开(公告)号：US12080426B2

公开(公告)日：2024-09-03

申请号：US17217082

申请日：2021-03-30

申请人： University of Florida Research Foundation, Inc.

发明人： Qing Lu ,  Shan Zhang ,  Tingting Hou

IPC分类号： G16B20/00 ,  G06N3/04 ,  G06N3/08 ,  G06T7/00 ,  G16B5/20 ,  G16H10/60 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30

CPC分类号： G16H50/20 ,  G06N3/04 ,  G06N3/08 ,  G06T7/0012 ,  G16B5/20 ,  G16H10/60 ,  G16H30/40 ,  G16H50/30 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30016

摘要： Various examples of methods and systems are provided related to functional deep neural networks (FDNNs), which can be used for high dimensional data analysis. In one example, a FDNN can be trained with a training set of omic data to produce a trained FDNN model. The likelihood of a condition can be determined based upon output indications of the FDNN corresponding to the one or more phenotypes, with the output indications based upon analysis of omic data including a multi-level omic profile from an individual by the trained FDNN. The FDNN model can include a series of basis functions as layers to capture complexity between the omic data with disease phenotypes. A treatment or prevention strategy for the individual can be identified based at least in part upon the likelihood of the condition.