Electronic terminal and medical inquiry method

An electronic terminal and probabilistic technology, applied in the field of Internet of Things, can solve the problem of low accuracy of diagnostic results

Active Publication Date: 2021-05-14
HISENSE
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] The present invention provides an electronic terminal and a medical inquiry method to solve the problem in the prior art that the accuracy of the diagnostic results output by the reinforcement learning network is not high

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  • Electronic terminal and medical inquiry method
  • Electronic terminal and medical inquiry method
  • Electronic terminal and medical inquiry method

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Embodiment Construction

[0076] In order to enable ordinary persons in the art to better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings.

[0077] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent w...

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Abstract

The invention relates to an electronic terminal and a medical inquiry method, relates to the technical field of medical inquiry, and is used for solving the problem of low accuracy of a diagnosis result output by a reinforcement learning network in the prior art. The method comprises the following steps: a processor is used for acquiring a disease probability and a disease factor probability by adopting an inquiry neural network model, acquiring another disease probability and another disease factor probability by adopting a knowledge graph, and determining feedback information of a next round according to a comprehensive disease probability corresponding to the two disease probabilities. According to the embodiment of the invention, the statistical dependency relationship of the diseases and the disease factors recorded in the knowledge graph is combined, so that the problem that the prior knowledge of the reinforcement learning model is insufficient is solved, and the accuracy of medical inquiry is improved.

Description

technical field [0001] The invention relates to the technical field of the Internet of Things, in particular to an electronic terminal and a medical inquiry method. Background technique [0002] An inquiry system for medical diagnosis can have a dialogue with a patient to obtain a complete description of the patient's symptoms and automatically make a diagnosis. The use of an inquiry system can significantly simplify the consultation process and reduce the cost of collecting information from patients. In addition, patient condition reports generated by the interrogation system can help doctors diagnose more effectively. [0003] In the existing medical inquiry system, the knowledge map method is used. The knowledge map method calculates the symptoms that should be asked in the next round according to the probability dependence relationship between the disease and the symptoms, and calculates the probability distribution of the disease. Reinforcement learning methods have al...

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Application Information

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IPC IPC(8): G16H40/67G16H50/20G06F16/332G06F16/36
CPCG16H40/67G16H50/20G06F16/3329G06F16/367
Inventor 刘奎刘宏举方鹏程
Owner HISENSE
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