公开(公告)号：US20190385696A1

公开(公告)日：2019-12-19

申请号：US16428715

申请日：2019-05-31

Applicant: Korea Advanced Institute of Science and Technology

Inventor： DongHo CHO ,  Hyein SEO ,  YongJoon SONG ,  GyuBum HAN ,  Dong Jin Ji

IPC: G16B5/20 ,  G16B5/30 ,  G16B35/10 ,  G16B40/00

Abstract: Provided is a method for diagnosing a disease risk based on complex genetic information network analysis. In the method for diagnosing a disease risk based on complex genetic information network analysis according to the present invention, it is possible to deduce a stable correlation with a disease from a small number of genetic information combination by introducing an optimization method or learning method, and it is possible to provide a genetic information correlation based on a network model. A diagnosis technology satisfying accuracy and economical efficiency enough to be commercially used in an actual medical field by using the correlation between the genetic information and the disease deduced in the present invention will be secured. Further, the biomarker deduced in the present invention will be commercially used in manufacturing a medical device including a diagnosis chip and terminal and in disease diagnosis service.

公开(公告)号：US20220246232A1

公开(公告)日：2022-08-04

申请号：US17168288

申请日：2021-02-05

Applicant: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY

Inventor： DongHo CHO ,  Dong Jin JI

IPC: G16B5/20 ,  G16B40/00

Abstract: Provided is a method for diagnosing a disease risk based on a complex biomarker network. More particularly, provided is a method for predicting or diagnosing a disease risk by constructing a complex disease relation network from biomarkers extracted from a liquid biological specimen and automatically extracting a disease marker from the complex disease relation network. It was confirmed that the method for predicting or diagnosing a disease risk using the biomarkers extracted from the liquid biological specimen developed according to the present invention applies an improved network analysis and learning method as compared to conventional methods, and thus enables disease-related diagnosis which shows high sensitivity and specificity even when only a few biomarkers are applied, which indicates that the method of the present invention shows superior extraction performance, compared to the methods using conventional variational dropout-based biomarker extraction.