Prediction of arrhythmia after intervention in children with atrial septal defect based on random forest

BMC Pediatrics

Yuhai Liu¹  Bo Song²  Hongxiao Sun³  Xiaowen Cui³  Gang Luo³  Silin Pan³ 

[1] Institute Oceanology, Chinese Academy of Sciences, 266071, Qingdao, China;Qingdao University of Science and Technology, 266061, Qingdao, China;Qingdao Women and Children’s Hospital, Qingdao University, 266034, Qingdao, China;

关键词: Atrial septal defect;    Interventional therapy;    Random forest;    Synthetic Minority Oversampling Technique algorithm;   

DOI  :  10.1186/s12887-021-02744-7

来源: Springer

【 摘 要 】

BackgroundUsing random forest to predict arrhythmia after intervention in children with atrial septal defect.MethodsWe constructed a prediction model of complications after interventional closure for children with atrial septal defect. The model was based on random forest, and it solved the need for postoperative arrhythmia risk prediction and assisted clinicians and patients’ families to make preoperative decisions.ResultsAvailable risk prediction models provided patients with specific risk factor assessments, we used Synthetic Minority Oversampling Technique algorithm and random forest machine learning to propose a prediction model, and got a prediction accuracy of 94.65 % and an Area Under Curve value of 0.8956.ConclusionsOur study was based on the model constructed by random forest, which can effectively predict the complications of arrhythmia after interventional closure in children with atrial septal defect.

【 授权许可】

CC BY