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Title:
DISEASE RISK PREDICTION METHOD AND SYSTEM BASED ON MULTI-MODAL FUSION
Document Type and Number:
WIPO Patent Application WO/2022/227294
Kind Code:
A1
Abstract:
A disease risk prediction method based on multi-modal fusion. The method comprises: acquiring EHR data of a patient, wherein the EHR data comprises structured data and unstructured data; inputting the EHR data into a disease risk prediction model, so as to obtain a disease risk prediction result; and outputting the disease risk prediction result, wherein execution steps of the disease risk prediction model comprise: extracting a structured data feature and an unstructured data feature; fusing the structured data feature and the unstructured data feature, and extracting a fused feature; and making a decision on the fused feature to obtain the disease risk prediction result. In addition, further disclosed are a disease risk prediction system based on multi-modal fusion and used for implementing the method, and a method for processing EHR data, a method for constructing a disease risk prediction model, and a computer device and a computer-readable storage medium, which can implement a method.

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Inventors:
LIU ZHI (CN)
LI YUJUN (CN)
HU XIFENG (CN)
HU WEIFENG (CN)
Application Number:
PCT/CN2021/106860
Publication Date:
November 03, 2022
Filing Date:
July 16, 2021
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Assignee:
UNIV SHANDONG (CN)
International Classes:
G16H10/60; G16H50/20
Foreign References:
CN113241135A2021-08-10
CN111916207A2020-11-10
CN109117864A2019-01-01
US20160342764A12016-11-24
Other References:
LAILA RASMY; YANG XIANG; ZIQIAN XIE; CUI TAO; DEGUI ZHI: "Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction", ARXIV.ORG, 22 May 2020 (2020-05-22), pages 1 - 23, XP081683869
Attorney, Agent or Firm:
JINAN SHENGDA INTELLECTUAL PROPERTY AGENCY CO., LTD. (CN)
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