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Open Set Medical Diagnosis

Open Set Medical Diagnosis

7 October 2019
Viraj Prabhu
A. Kannan
Geoffrey Tso
Namit Katariya
Manish Chablani
David Sontag
X. Amatriain
ArXiv (abs)PDFHTML

Papers citing "Open Set Medical Diagnosis"

12 / 12 papers shown
Title
Federated Learning: Challenges, Methods, and Future Directions
Federated Learning: Challenges, Methods, and Future Directions
Tian Li
Anit Kumar Sahu
Ameet Talwalkar
Virginia Smith
FedML
129
4,540
0
21 Aug 2019
FADL:Federated-Autonomous Deep Learning for Distributed Electronic
  Health Record
FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record
Dianbo Liu
Timothy A. Miller
R. Sayeed
K. Mandl
FedMLOOD
57
61
0
28 Nov 2018
Reducing Network Agnostophobia
Reducing Network Agnostophobia
A. Dhamija
Manuel Günther
Terrance E. Boult
AAMLUQCV
73
305
0
09 Nov 2018
Learning from the experts: From expert systems to machine-learned
  diagnosis models
Learning from the experts: From expert systems to machine-learned diagnosis models
Murali Ravuri
A. Kannan
Geoffrey Tso
X. Amatriain
38
18
0
21 Apr 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
175
2,149
0
24 Jan 2018
Training Confidence-calibrated Classifiers for Detecting
  Out-of-Distribution Samples
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples
Kimin Lee
Honglak Lee
Kibok Lee
Jinwoo Shin
OODD
120
882
0
26 Nov 2017
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) Analysis
B. Shickel
P. Tighe
A. Bihorac
Parisa Rashidi
BDL
100
1,119
0
12 Jun 2017
Enhancing The Reliability of Out-of-distribution Image Detection in
  Neural Networks
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
Shiyu Liang
Yixuan Li
R. Srikant
UQCVOODD
171
2,081
0
08 Jun 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCVBDL
842
5,841
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCVBDL
852
9,346
0
06 Jun 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
2.0K
150,312
0
22 Dec 2014
Towards Open World Recognition
Towards Open World Recognition
Abhijit Bendale
Terrance Boult
84
566
0
18 Dec 2014
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