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A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis

A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis

14 August 2020
Maria Hügle
Gabriel Kalweit
T. Huegle
Joschka Boedecker
    BDL
ArXiv (abs)PDFHTML

Papers citing "A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis"

15 / 15 papers shown
Modelling Patient Trajectories Using Multimodal Information
Modelling Patient Trajectories Using Multimodal InformationJournal of Biomedical Informatics (JBI), 2022
J. F. Silva
S. Matos
145
16
0
09 Sep 2022
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning
  in Autonomous Driving
Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous DrivingIEEE International Conference on Robotics and Automation (ICRA), 2019
M. Huegle
Gabriel Kalweit
M. Werling
Joschka Boedecker
3DPC
196
38
0
30 Sep 2019
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving
Dynamic Input for Deep Reinforcement Learning in Autonomous DrivingIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2019
Maria Hügle
Gabriel Kalweit
Branka Mirchevska
M. Werling
Joschka Boedecker
189
64
0
25 Jul 2019
BEHRT: Transformer for Electronic Health Records
BEHRT: Transformer for Electronic Health RecordsScientific Reports (Sci Rep), 2019
Yikuan Li
Shishir Rao
J. R. A. Solares
A. Hassaine
D. Canoy
Yajie Zhu
K. Rahimi
G. Salimi-Khorshidi
OOD
644
607
0
22 Jul 2019
Learning the Graphical Structure of Electronic Health Records with Graph
  Convolutional Transformer
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional TransformerAAAI Conference on Artificial Intelligence (AAAI), 2019
Edward Choi
Zhen Xu
Yujia Li
Michael W. Dusenberry
Gerardo Flores
Yuan Xue
Andrew M. Dai
MedIm
304
288
0
11 Jun 2019
Learning Hierarchical Representations of Electronic Health Records for
  Clinical Outcome Prediction
Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome PredictionAmerican Medical Informatics Association Annual Symposium (AMIA), 2019
Luchen Liu
Haoran Li
Zhiting Hu
Haoran Shi
Zichang Wang
Jian Tang
Ming Zhang
BDL
204
32
0
20 Mar 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CEGNN
2.4K
6,769
0
20 Dec 2018
Learning the Joint Representation of Heterogeneous Temporal Events for
  Clinical Endpoint Prediction
Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint PredictionAAAI Conference on Artificial Intelligence (AAAI), 2018
Luchen Liu
Jianhao Shen
Ming Zhang
Zichang Wang
Jian Tang
191
47
0
13 Mar 2018
Scalable and accurate deep learning for electronic health records
Scalable and accurate deep learning for electronic health records
A. Rajkomar
Eyal Oren
Kai Chen
Andrew M. Dai
Nissan Hajaj
...
A. Butte
M. Howell
Claire Cui
Greg S. Corrado
Jeffrey Dean
OODBDL
507
2,608
0
24 Jan 2018
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for
  Electronic Health Record (EHR) Analysis
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) AnalysisIEEE journal of biomedical and health informatics (IEEE JBHI), 2017
B. Shickel
P. Tighe
A. Bihorac
Parisa Rashidi
BDL
684
1,379
0
12 Jun 2017
Deep Sets
Deep Sets
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
1.8K
2,849
0
10 Mar 2017
Deepr: A Convolutional Net for Medical Records
Deepr: A Convolutional Net for Medical Records
Phuoc Nguyen
T. Tran
N. Wickramasinghe
Svetha Venkatesh
MedIm
338
394
0
26 Jul 2016
Recurrent Neural Networks for Multivariate Time Series with Missing
  Values
Recurrent Neural Networks for Multivariate Time Series with Missing ValuesScientific Reports (Sci Rep), 2016
Zhengping Che
S. Purushotham
Dong Wang
David Sontag
Yan Liu
AI4TS
775
2,300
0
06 Jun 2016
Learning to Diagnose with LSTM Recurrent Neural Networks
Learning to Diagnose with LSTM Recurrent Neural Networks
Zachary Chase Lipton
David C. Kale
Charles Elkan
R. Wetzel
759
1,185
0
11 Nov 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014
Diederik P. Kingma
Jimmy Ba
ODL
5.0K
164,701
0
22 Dec 2014
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