ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1703.08705
  4. Cited By
Comparing Rule-Based and Deep Learning Models for Patient Phenotyping

Comparing Rule-Based and Deep Learning Models for Patient Phenotyping

25 March 2017
Sebastian Gehrmann
Franck Dernoncourt
Yeran Li
Eric T. Carlson
Joy T. Wu
Jonathan Welt
J. Foote
E. Moseley
David W. Grant
P. Tyler
Leo Anthony Celi
ArXivPDFHTML

Papers citing "Comparing Rule-Based and Deep Learning Models for Patient Phenotyping"

14 / 14 papers shown
Title
"What is Relevant in a Text Document?": An Interpretable Machine
  Learning Approach
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach
L. Arras
F. Horn
G. Montavon
K. Müller
Wojciech Samek
69
288
0
23 Dec 2016
Deep Survival Analysis
Deep Survival Analysis
Rajesh Ranganath
A. Perotte
Noémie Elhadad
David M. Blei
165
199
0
06 Aug 2016
LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in
  Recurrent Neural Networks
LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks
Hendrik Strobelt
Sebastian Gehrmann
Hanspeter Pfister
Alexander M. Rush
HAI
61
83
0
23 Jun 2016
Explaining Predictions of Non-Linear Classifiers in NLP
Explaining Predictions of Non-Linear Classifiers in NLP
L. Arras
F. Horn
G. Montavon
K. Müller
Wojciech Samek
FAtt
76
117
0
23 Jun 2016
De-identification of Patient Notes with Recurrent Neural Networks
De-identification of Patient Notes with Recurrent Neural Networks
Franck Dernoncourt
Ji Young Lee
Özlem Uzuner
Peter Szolovits
OOD
57
376
0
10 Jun 2016
"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
FAtt
FaML
1.2K
16,976
0
16 Feb 2016
Understanding Neural Networks Through Deep Visualization
Understanding Neural Networks Through Deep Visualization
J. Yosinski
Jeff Clune
Anh Totti Nguyen
Thomas J. Fuchs
Hod Lipson
FAtt
AI4CE
122
1,872
0
22 Jun 2015
Visualizing and Understanding Neural Models in NLP
Visualizing and Understanding Neural Models in NLP
Jiwei Li
Xinlei Chen
Eduard H. Hovy
Dan Jurafsky
MILM
FAtt
75
706
0
02 Jun 2015
Extraction of Salient Sentences from Labelled Documents
Extraction of Salient Sentences from Labelled Documents
Misha Denil
Alban Demiraj
Nando de Freitas
73
137
0
21 Dec 2014
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
621
13,422
0
25 Aug 2014
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAI
OCL
392
33,521
0
16 Oct 2013
ADADELTA: An Adaptive Learning Rate Method
ADADELTA: An Adaptive Learning Rate Method
Matthew D. Zeiler
ODL
150
6,624
0
22 Dec 2012
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
453
7,661
0
03 Jul 2012
Natural Language Processing (almost) from Scratch
Natural Language Processing (almost) from Scratch
R. Collobert
Jason Weston
Léon Bottou
Michael Karlen
Koray Kavukcuoglu
Pavel P. Kuksa
186
7,725
0
02 Mar 2011
1