On the Effectiveness of Deep Representation Learning: The Atrial Fibrillation Case

被引：7

作者：

Gadaleta, Matteo ^{[1
]}

Rossi, Michele ^{[1
]}

Topol, Eric J. ^{[2
]}

Steinhubl, Steven R. ^{[2
]}

Quer, Giorgio ^{[2
]}

机构：

[1] Univ Padua, Padua, Italy

[2] Scripps Res Translat Inst, La Jolla, CA USA

来源：

COMPUTER | 2019年 / 52卷 / 11期

基金：

美国国家卫生研究院;

关键词：

MEDICINE; CLASSIFICATION;

D O I：

10.1109/MC.2019.2932716

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The automatic, unsupervised analysis of biomedical time series is vital for diagnostic and preventive medicine, enabling fast and reliable data processing that reveals clinical insights without human intervention. This article explores and quantifies the benefits of modern deeplearning architectures of varying degrees of complexity. © 1970-2012 IEEE.

引用

页码：18 / 29

页数：12

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