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Drug recommendation evidence-based support method and device, equipment and storage medium

A drug and prescription technology, applied in the fields of medicine and smart medical care, can solve the problems of not being able to recommend current patient prescriptions, affecting the promotion and application of artificial intelligence, and poor prognosis, achieving the effects of high reliability, convenient operation, and improved accuracy.

Pending Publication Date: 2021-12-03
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most of the currently existing content about machine learning interpretability is about the internal structure of the model, or giving a global ranking of feature importance. These methods are not user-centered explanations. When the drug recommendation system recommends several prescriptions, The doctor does not know which prescription is the best for the current patient, and which prescription is more suitable for the current patient, so they cannot make accurate recommendations for the current patient with reason and evidence, and the prognosis is poor, which in turn cannot help the doctor to make a prescription. The final decision has seriously affected the promotion and application of artificial intelligence in the medical field

Method used

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  • Drug recommendation evidence-based support method and device, equipment and storage medium
  • Drug recommendation evidence-based support method and device, equipment and storage medium
  • Drug recommendation evidence-based support method and device, equipment and storage medium

Examples

Experimental program
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Embodiment 1

[0052] see figure 1 and figure 2, in this embodiment, an evidence-based support method for drug recommendation is provided, which is used to overcome the inaccurate recommendation caused by only relying on the drug recommendation model to recommend prescriptions in the prior art, so as to improve the accuracy of drug recommendation. At the same time, it needs to be explained Yes, the present invention also solves the problem that the drug recommendation cannot be based on evidence in the prior art, so that the drug recommendation is justified, so as to improve the accuracy and prognostic effect of the drug recommendation. An evidence-based support method for drug recommendation that sorts the recommended prescriptions in the recommended prescription list output by the drug recommendation model.

[0053] Specifically, the drug recommendation evidence-based support methods described in the present invention include:

[0054] 1) Use the drug recommendation model to obtain the ...

Embodiment 2

[0101] refer to Figure 4 , the drug recommendation evidence-based support device of the present invention, comprising:

[0102] The first obtaining module 1 is used to obtain the recommended prescription list of the target patient by using the drug recommendation model;

[0103] Determining module 2, used to obtain several similar patients of the target patient;

[0104] The second acquisition module 3 is used to acquire the characteristic information, prescription information and prognosis information of each similar patient;

[0105] Building block 4, for constructing a logistic regression model according to the characteristic information, prescription information and prognosis information of each similar patient;

[0106] The sorting module 6 is used to sort the recommended prescriptions in the recommended prescription list of the target patient by using the logistic regression model to obtain the sorting results of the recommended prescriptions;

[0107] The recommenda...

Embodiment 3

[0125] A computer device, comprising a memory, a processor, and a computer program stored in the memory and operable on the processor, when the processor executes the computer program, implements the method of evidence-based support for drug recommendation Step, wherein, the memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk memory, etc.; the processor, the network interface, and the memory are connected to each other through an internal bus, and the internal bus It can be an industry standard architecture bus, a peripheral component interconnection standard bus, an extended industry standard architecture bus, etc. The bus can be divided into address bus, data bus, control bus, etc. The memory is used to store programs, specifically, the programs may include program codes, and the program codes include computer operation instructions. Storage, which can include internal memory and nonvol...

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Abstract

The invention discloses a medicine recommendation evidence-based support method and device, equipment and a storage medium. The method comprises the following steps: acquiring a recommended prescription list of a target patient by utilizing a medicine recommendation model; acquiring N similar patients of the target patient, wherein N is a positive integer; acquiring feature information, prescription information and prognosis information of the N similar patients; constructing a logistic regression model according to the feature information, the prescription information and the prognosis information of the N similar patients; sorting the recommended prescriptions in the recommended prescription list of the target patient by using the logistic regression model to obtain a sorting result of the recommended prescriptions. According to the method, the device, the equipment and the storage medium, prescription recommendation can be accurately carried out on the patient.

Description

technical field [0001] The invention belongs to the technical field of medicine and smart medical care, and relates to an evidence-based support method, device, equipment and storage medium for drug recommendation. Background technique [0002] Machine learning technology has been applied to all aspects of the medical field, such as auxiliary diagnosis, intelligent imaging, drug development, electronic medical record generation, and drug recommendation. While the push for machine learning to go deeper in healthcare comes with growing calls for regulation and accountability of machine learning and artificial intelligence-based systems in healthcare. For doctors, machine learning models are a black box, and interpretable machine learning models can help maintain the safety and reliability of machine learning systems. Most of the currently existing content about machine learning interpretability is about the internal structure of the model, or giving a global ranking of featur...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G16H20/10
CPCG16H50/20G16H20/10
Inventor 赵婷婷孙行智徐卓扬刘卓
Owner PING AN TECH (SHENZHEN) CO LTD
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