most citedIdentification of 27 abnormalities from multi-lead ECG signals: An ensembled Se-ResNet framework with Sign Loss function

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021

Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals

Xiang Lan, Dianwen Ng, Shenda Hong +1

Learning information-rich and generalizable representations effectively from unlabeled multivariate cardiac signals to identify abnormal heart rhythms (cardiac arrhythmias) is valu…

eess.SP2021★ 2 cited

Identification of 27 abnormalities from multi-lead ECG signals: An ensembled Se-ResNet framework with Sign Loss function

Zhaowei Zhu, Xiang Lan, Tingting Zhao +8

Cardiovascular disease is a major threat to health and one of the primary causes of death globally. The 12-lead ECG is a cheap and commonly accessible tool to identify cardiac abno…