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2102.06761
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MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset
12 February 2021
Chuizheng Meng
Loc Trinh
Nan Xu
Yan Liu
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Papers citing
"MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset"
14 / 14 papers shown
Title
Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
FaML
47
191
0
03 Nov 2020
Measuring Unfairness through Game-Theoretic Interpretability
Juliana Cesaro
Fabio Gagliardi Cozman
FAtt
54
13
0
12 Oct 2019
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III
Shirly Wang
Matthew B. A. McDermott
Geeticka Chauhan
Michael C. Hughes
Tristan Naumann
Marzyeh Ghassemi
45
207
0
19 Jul 2019
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data
Tian Guo
Tao R. Lin
Nino Antulov-Fantulin
AI4TS
47
155
0
28 May 2019
CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models
Shubham Sharma
Jette Henderson
Joydeep Ghosh
33
87
0
20 May 2019
Attention is not Explanation
Sarthak Jain
Byron C. Wallace
FAtt
87
1,307
0
26 Feb 2019
Clinical Intervention Prediction and Understanding using Deep Networks
Harini Suresh
Nathan Hunt
Alistair E. W. Johnson
Leo Anthony Celi
Peter Szolovits
Marzyeh Ghassemi
OOD
52
131
0
23 May 2017
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
123
3,848
0
10 Apr 2017
Multitask learning and benchmarking with clinical time series data
Hrayr Harutyunyan
Hrant Khachatrian
David C. Kale
Greg Ver Steeg
Aram Galstyan
OOD
AI4TS
120
867
0
22 Mar 2017
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
122
5,920
0
04 Mar 2017
Inherent Trade-Offs in the Fair Determination of Risk Scores
Jon M. Kleinberg
S. Mullainathan
Manish Raghavan
FaML
84
1,762
0
19 Sep 2016
The Mythos of Model Interpretability
Zachary Chase Lipton
FaML
123
3,672
0
10 Jun 2016
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
181
4,653
0
21 Dec 2014
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
329
15,825
0
12 Nov 2013
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