Models for predicting treatment efficacy of antiepileptic drugs and prognosis of treatment withdrawal in epilepsy patients

作     者：Shijun Yang Bin Wang Xiong Han 

作者机构：Department of NeurologyPeople’s Hospital of Zhengzhou UniversityHenan Provincial People’s HospitalZhengzhou 450003China 

出 版 物：《Acta Epileptologica》 (癫痫学报（英文）)

年 卷 期：2021年第3卷第1期

页      面：1-6页

学科分类：1002[医学-临床医学] 10[医学] 

基　　金：This study was supported by Joint Construction Project of Province and Ministry in Henan Province(Grant number SB201901074) 

主　　题：Prediction model Machine learning Antiepileptic drugs Drug response Withdrawal reaction 

摘      要：Although anteplleptlc drugs(AEDs)are the most effective treatment for epllepsy,30-40%of patlents with epllepsy would develop drug-efacory *** accurate,prellminary predlctlon of the efflcacy of AEDs has great clinical signflcance for patent treatment and *** studles have developed statstical models and machine-learning algorithms(MLAS)to predlct the fficacy of AEDs treatment and the progression of disease ater treatment withdrawal,In order to provlde asstance for makng cInlcal decslons In the alm of precse,personalzed treatment The fleld of predcton models with statstical models and MLAs s atracting growing Interest and s developing *** s more,more and more studles focus on the external valldation of the exlsting model In this revlew,we will glve a brlef overvlew of recent developments In this discipline.