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Medication decision-making method and system based on deep learning

A technology of deep learning and decision-making methods, applied in the field of medical artificial intelligence-assisted diagnosis, can solve problems that affect the accuracy of medication decisions and cannot be widely used, and achieve high recommendation accuracy and improve stability.

Active Publication Date: 2020-09-22
CENT SOUTH UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

However, due to the sparsity of medication records, the method of implicit feedback based on the doctor's empirical preference for medication limits the performance of the efficacy prediction model, thereby affecting the accuracy of medication decisions
Therefore, the existing machine learning-based medication decision-making system cannot be widely used in actual clinical practice.

Method used

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  • Medication decision-making method and system based on deep learning
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  • Medication decision-making method and system based on deep learning

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Embodiment Construction

[0050] The following describes the technical solutions in the embodiments of the present invention clearly and completely with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments produced by those of ordinary skill in the art without creative work fall within the protection scope of the present invention. In addition, it should be noted that the "said..." in the specific implementation content only refers to the technical attributes or features of the present invention.

[0051] In order to use the medication decision system to be truly clinically applied to assist doctors in making decisions about medication regimens suitable for patients, the present invention provides a medication decision method based on deep learning. Through the medication decisio...

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Abstract

The invention provides a medication decision-making method and system based on deep learning. The method comprises the following steps: collecting patient-related information, medication scheme-related information and actual curative effect evaluation information of a medication scheme on an actual curative effect of a patient to obtain an analysis data set; analyzing and processing the analysis data set through a constructed curative effect prediction model so as to predict predicted curative effect evaluation information of each medication scheme for different patient treatment effects; andrecommending the medication scheme suitable for the personalized requirements of the patient to the patient according to the predicted curative effect evaluation information. The medication decision-making method and system have high accuracy and stability during medication scheme recommendation, and are suitable for medical clinical application.

Description

Technical field [0001] The invention belongs to the technical field of medical artificial intelligence-assisted diagnosis, and specifically relates to a method and system for medication decision-making based on deep learning. Background technique [0002] In medical artificial intelligence research, the intelligent auxiliary diagnosis system can help doctors make analysis and diagnosis of the condition, help improve the efficiency of patients' medical treatment, shorten the time and cycle of patients' diagnosis and treatment, and effectively reduce the workload of doctors , It can alleviate the current shortage of social medical resources. [0003] The diversity of drugs and the different pathological characteristics of patients complicate drug treatment. Various influencing factors can affect the dosage of the drug. It is often not enough to rely solely on the personal judgment of the physician. It may be due to incomplete information collection or insufficient personal knowledge ...

Claims

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Application Information

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IPC IPC(8): G16H50/70G16H50/20G16H20/10G16H10/60G06N3/02G06K9/62
CPCG16H50/70G16H50/20G16H10/60G16H20/10G06N3/02G06F18/214Y02A90/10
Inventor 吴嘉余庚花张璇田晓明常柳庄庆贺
Owner CENT SOUTH UNIV
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