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Patent Searching and Data


Title:
COMPLICATION RISK-BASED CHRONIC DISEASE MEDICAL INSURANCE COST PREDICTION METHOD, AND RELATED DEVICE
Document Type and Number:
WIPO Patent Application WO/2021/203997
Kind Code:
A1
Abstract:
A complication risk-based chronic disease medical insurance cost prediction method, and a related device. A processor of the device is used for: determining the co-occurrence frequency between different complications of each chronic disease patient, and determining a representation vector of each node in a graph network structure according to the co-occurrence frequency; inputting the representation vector and historical chronic disease data into a multilayer perceptron model, and determining a complication prediction model; inputting the historical chronic disease data and the probability of each chronic disease patient suffering from complications into a first recurrent neural network model, and determining a medical insurance cost prediction model; and inputting health-seeking data of a chronic disease patient to be tested into the complication prediction model and the medical insurance cost prediction model, so as to obtain the probability of the risk that the chronic disease patient to be tested suffers from complications and a medical insurance cost prediction result. The medical insurance costs are predicted on the basis of the probability of the risk that a chronic disease patient suffers from complications, thereby improving the prediction accuracy. The data can be stored in a blockchain.

Inventors:
XU XIAO (CN)
XU XIAN (CN)
SUN YUYAO (CN)
LI XIANG (CN)
XIE GUOTONG (CN)
Application Number:
PCT/CN2021/083523
Publication Date:
October 14, 2021
Filing Date:
March 29, 2021
Export Citation:
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Assignee:
PING AN TECH SHENZHEN CO LTD (CN)
International Classes:
G16H50/30; G16H10/60; G16H40/20
Foreign References:
CN112037918A2020-12-04
CN109616216A2019-04-12
JP6482803B22019-03-13
CN106407686A2017-02-15
CN111275558A2020-06-12
CN111297329A2020-06-19
Attorney, Agent or Firm:
SCIHEAD IP LAW FIRM (CN)
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