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Electrocardiographic Deep Learning for Predicting Post-Procedural
  Mortality

Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality

30 April 2022
David Ouyang
J. Theurer
N. Stein
J. Hughes
P. Elias
Bryan He
N. Yuan
Grant Duffy
R. Sandhu
J. Ebinger
P. Botting
Melvin Jujjavarapu
B. Claggett
J. Tooley
T. Poterucha
Jonathan H. Chen
M. Nurok
M. Perez
A. Perotte
J. Zou
N. Cook
S. Chugh
Susan Cheng
C. Albert
ArXiv (abs)PDFHTML

Papers citing "Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality"

5 / 5 papers shown
Title
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan
Quoc V. Le
3DVMedIm
172
18,224
0
28 May 2019
Deep neural networks can predict mortality from 12-lead
  electrocardiogram voltage data
Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
S. Raghunath
Alvaro E. Ulloa Cerna
Linyuan Jing
David P. vanMaanen
Joshua V. Stough
...
B. Delisle
Amro Alsaid
Dominik Beer
C. Haggerty
Brandon K. Fornwalt
43
185
0
15 Apr 2019
MobileNetV2: Inverted Residuals and Linear Bottlenecks
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
218
19,353
0
13 Jan 2018
Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs
  using Deep Learning
Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learning
Ryan Poplin
A. Varadarajan
Katy Blumer
Yun-Hui Liu
M. McConnell
G. Corrado
L. Peng
D. Webster
MedIm
73
1,340
0
31 Aug 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
1