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    Predicting All-Cause Mortality Risk in Atrial Fibrillation Patients: A Novel LASSO-Cox Model Generated From a Prospective Dataset by Yu Chen, Shiwan Wu, Jianfeng Ye, Muli Wu, Zhongbo Xiao, Xiaobin Ni, Bin Wang, Chang Chen, Yequn Chen, Yequn Chen, Yequn Chen, Xuerui Tan, Xuerui Tan, Xuerui Tan, Ruisheng Liu

    Published 2021-10-01
    “…Background: Although mortality remains high in patients with atrial fibrillation (AF), there have been limited studies exploring machine learning (ML) models on mortality risk prediction in patients with AF.Objectives: This study sought to develop an ML model that captures important variables in order to predict all-cause mortality in AF patients.Methods: In this single center prospective study, an ML-based mortality prediction model was developed and validated using a dataset of 2,012 patients who experienced AF from November 2018 to February 2020 at the First Affiliated Hospital of Shantou University Medical College. The dataset was randomly divided into a training set (70%, n = 1,223) and a validation set (30%, n = 552). …”
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