Table 4 Compare of Acc and \(F_1\)-score to other models in the PhysioNet Challenge 2017 dataset.

Dighanchal Banerjee et al²⁸

AF classification

SNN

–

0.770

Wang et al²⁹

AF detection

DPRNN

0.829

0.845

Christopher Snyder et al¹⁶

AF classification

DNN

–

0.740

Fayyazifar³⁰

AF detection

NAS

0.824

0.842

Chen et al³¹

AF detection

XGBoost

0.805

0.838

Zihlmann et al³²

AF classification

CRNN

0.746

0.792

Aoxiang Zhang et al³³

AF classification

RANet

0.817

-

Jia Xie et al³⁴

AF classification

Bi-LSTMAttns

0.823

0.844

Yongyong Chen et al³⁵

AF detection

QRS detection

-

0.846

Ours

AF classification

LRA-autoencoder

0.843

0.850