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Epilepsy medication recommendation method and system

A recommendation method and recommendation system technology, applied in the fields of biomedicine and data processing, can solve the problems of individual differences in the efficacy of antiepileptic drugs, the complexity of treatment plans, etc., to reduce adverse reactions, improve epilepsy control rate, and improve the efficiency of diagnosis and treatment.

Pending Publication Date: 2020-07-28
SHANDONG UNIV
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AI Technical Summary

Problems solved by technology

These factors act independently or interact with each other, resulting in individual differences in the efficacy of various antiepileptic drugs and the complexity of treatment options

Method used

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  • Epilepsy medication recommendation method and system
  • Epilepsy medication recommendation method and system
  • Epilepsy medication recommendation method and system

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Experimental program
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Embodiment 1

[0059] 1. Research object

[0060] 1.1 Patients with epilepsy

[0061] The research team has established an epilepsy treatment observation and follow-up cohort since 2008. The patients are all epilepsy patients diagnosed by neurologists in Linyi People's Hospital and receiving antiepileptic drug treatment in the hospital for a long time. The vast majority of patients go to the hospital for reexamination on a regular basis, accept the doctor's instructions for medication and receive follow-up visits; those who do not go to the hospital for reexamination in time will be followed up by telephone by a special person to understand the treatment effect.

[0062] 1.2 Diagnostic criteria

[0063] According to the classification and diagnostic criteria of the International League Against Epilepsy (ILAE), epilepsy was diagnosed by clinicians in combination with clinical manifestations, EEG and imaging examinations, and an appropriate drug regimen was selected according to the seizures ...

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Abstract

The invention provides an epilepsy medication recommendation method and system, and belongs to the technical field of biomedicine and data processing. According to the invention, deep sequencing is carried out on an antiepileptic drug metabolic enzyme gene, a transporter gene and a drug action target gene, related coding gene polymorphic sites are screened, a Bayesian accumulation regression treemodel and random forest regression are utilized to obtain a personalized medication scheme depending on individual genes, and a subset with high treatment effect is identified, so that clinical medication is guided in a targeted manner, the epilepsy control rate is improved, adverse reactions are reduced, the time for doctors and patients to explore the optimal treatment scheme is shortened, the diagnosis and treatment efficiency is improved, and the method has good practical application value.

Description

technical field [0001] The invention belongs to the technical field of biomedicine and data processing, and in particular relates to a method and system for recommending epilepsy medication. Background technique [0002] The information disclosed in this background section is only intended to increase the understanding of the general background of the present invention, and is not necessarily to be regarded as an acknowledgment or any form of suggestion that the information constitutes the prior art that is already known to those skilled in the art. [0003] Epilepsy is a common nervous system disease with various etiologies, high incidence, long course and low cure rate. The pathogenesis of epilepsy is not yet clear, and it is mainly believed that the imbalance between excitation and inhibition of the central nervous system leads to epilepsy, which is closely related to ion channels, neurotransmitter imbalance, glial cells and genetics. [0004] Seizures are mainly control...

Claims

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Application Information

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IPC IPC(8): G16H70/20G16H70/40G16H70/60G16B20/20G16B40/00
CPCG16H70/20G16H70/40G16H70/60G16B20/20G16B40/00
Inventor 薛付忠车峰远季晓康
Owner SHANDONG UNIV
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