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Medical case knowledge recommendation method and system considering implicit feedback and human-computer interaction

An implicit feedback, human-computer interaction technology, applied in computer-aided medical procedures, medical data mining, medical informatics, etc., can solve the problem of unable to recommend personalized cases, protect personal privacy, etc., to strengthen human-computer interaction. , The recommendation results are accurate and meet the personalized effect

Pending Publication Date: 2021-11-12
HEFEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the deficiencies of the existing technology, the present invention provides a medical case knowledge recommendation method and system considering implicit feedback and human-computer interaction, which solves the problem that the existing medical case knowledge recommendation technology cannot accurately recommend personalized cases for doctor users. while protecting personal privacy

Method used

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  • Medical case knowledge recommendation method and system considering implicit feedback and human-computer interaction
  • Medical case knowledge recommendation method and system considering implicit feedback and human-computer interaction
  • Medical case knowledge recommendation method and system considering implicit feedback and human-computer interaction

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Embodiment 1

[0089] First, see figure 1 , the present invention first proposes a medical case knowledge recommendation method considering implicit feedback and human-computer interaction, the method comprising:

[0090] S1. Obtain historical behavior data of user browsing cases and perform preprocessing and encryption processing; the historical behavior data includes explicit feedback data and implicit feedback data;

[0091] S2. Obtain the user's case scoring matrix and the similarity between different cases based on the explicit feedback data, and obtain the user-case interaction matrix based on the implicit feedback data using the hybrid recommendation model of GMF and MLP that integrates the attention mechanism , and encrypting the user-case interaction matrix and case data;

[0092] S3. Obtain a preliminary recommendation list based on the similarity, the user's case scoring matrix, and the user-case interaction matrix;

[0093] S4. Obtain a final recommendation list based on the pr...

Embodiment 2

[0229] In the second aspect, the present invention also proposes a medical case knowledge recommendation system considering implicit feedback and human-computer interaction, the system comprising:

[0230] The data acquisition and preprocessing module is used to acquire the historical behavior data of user browsing cases and perform preprocessing and encryption processing; the historical behavior data includes explicit feedback data and implicit feedback data;

[0231] The data feature extraction and encryption module is used to obtain the user's case scoring matrix and the similarity between different cases based on the explicit feedback data, and use the hybrid recommendation of GMF and MLP that integrates the attention mechanism based on the implicit feedback data The model acquires a user-case interaction matrix, and encrypts the user-case interaction matrix and case data;

[0232] A preliminary recommendation list acquisition module, configured to obtain a preliminary rec...

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Abstract

The invention provides a medical case knowledge recommendation method and system considering implicit feedback and human-computer interaction, and relates to the technical field of medical data processing. According to the method, historical behavior data of case browsing of a user is collected, preprocessed and encrypted, then explicit and implicit feedback data are processed by adopting a similarity calculation algorithm and a collaborative filtering algorithm fused by a multilayer neural network fused with an attention mechanism, the data processing result is encrypted by using a differential privacy protection model, and finally a personalized accurate case recommendation list suitable for the user is determined based on the processing results of the explicit and implicit feedback data in combination with a man-machine interaction behavior. According to the technical scheme, the personal privacy of the user and the patient is protected while personalized cases are accurately recommended for the user, and the comprehensive performance is excellent.

Description

technical field [0001] The invention relates to the technical field of medical data processing, in particular to a medical case knowledge recommendation method and system considering implicit feedback and human-computer interaction. Background technique [0002] The rapid development of the Internet has produced a large amount of data and information, and people are increasingly relying on these data and information. Most network applications recommend relevant information to people based on various recommendation systems and algorithms to meet the needs of different users. For example, in the medical and health field, based on the physiological data and disease characteristics of the human body, the case knowledge recommendation system can be used to match the appropriate treatment case from the case knowledge base and recommend it to the individual, and refer to the case to treat the individual. [0003] At present, in the field of medical and health care, the research an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/70G06F16/9536G06F21/62G06F21/60G06N3/04
CPCG16H50/70G06F16/9536G06F21/6245G06F21/602G06F21/604G06F2221/2141G06N3/045
Inventor 顾东晓钱锦刘虎李敏丁帅李霄剑欧阳波鲁超赵卉刘红艳赵旺苏凯翔黄智勇丁彬彬周翔程玮玲
Owner HEFEI UNIV OF TECH
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