Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1905.05134
Cited By
v1
v2 (latest)
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
13 May 2019
S. Tonekaboni
Shalmali Joshi
M. Mccradden
Anna Goldenberg
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use"
39 / 39 papers shown
Title
ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive Learning
Siyang Song
David Chen
Thomas Statchen
Michael C. Burkhart
Nipun Bhandari
Bashar Ramadan
Brett Beaulieu-Jones
115
1
0
11 Apr 2025
No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism
Yubo Li
Xinyu Yao
R. Padman
FAtt
AI4TS
83
0
0
25 Mar 2025
Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction
Leisheng Yu
Yanxiao Cai
Minxing Zhang
Helen Zhou
FAtt
451
0
0
15 Feb 2025
Tackling COVID-19 through Responsible AI Innovation: Five Steps in the Right Direction
David Leslie
183
67
0
15 Aug 2020
The Pragmatic Turn in Explainable Artificial Intelligence (XAI)
Andrés Páez
66
196
0
22 Feb 2020
Attention is not Explanation
Sarthak Jain
Byron C. Wallace
FAtt
148
1,329
0
26 Feb 2019
On the consistency of supervised learning with missing values
Julie Josse
Jacob M. Chen
Nicolas Prost
Erwan Scornet
Gaël Varoquaux
101
116
0
19 Feb 2019
Measuring Patient Similarities via a Deep Architecture with Medical Concept Embedding
Zihao Zhu
Changchang Yin
B. Qian
Yu Cheng
Jishang Wei
Fei Wang
60
118
0
09 Feb 2019
Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making
Carrie J. Cai
Emily Reif
Narayan Hegde
J. Hipp
Been Kim
...
Martin Wattenberg
F. Viégas
G. Corrado
Martin C. Stumpe
Michael Terry
107
403
0
08 Feb 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning
Peter F. Schulam
Suchi Saria
OOD
101
104
0
02 Jan 2019
ClinicalVis: Supporting Clinical Task-Focused Design Evaluation
Marzyeh Ghassemi
Mahima Pushkarna
James Wexler
Jesse Johnson
P. Varghese
39
19
0
13 Oct 2018
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAtt
AAML
XAI
152
1,970
0
08 Oct 2018
Model Cards for Model Reporting
Margaret Mitchell
Simone Wu
Andrew Zaldivar
Parker Barnes
Lucy Vasserman
Ben Hutchinson
Elena Spitzer
Inioluwa Deborah Raji
Timnit Gebru
140
1,908
0
05 Oct 2018
Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure
Besmira Nushi
Ece Kamar
Eric Horvitz
42
141
0
19 Sep 2018
RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data
Yanbo Xu
Siddharth Biswal
S. Deshpande
K. Maher
Jimeng Sun
67
168
0
23 Jul 2018
RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records
Bum Chul Kwon
Min-Je Choi
J. Kim
Edward Choi
Young Bin Kim
Soonwook Kwon
Jimeng Sun
Jaegul Choo
69
252
0
28 May 2018
Manipulating and Measuring Model Interpretability
Forough Poursabzi-Sangdeh
D. Goldstein
Jake M. Hofman
Jennifer Wortman Vaughan
Hanna M. Wallach
99
701
0
21 Feb 2018
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
148
3,979
0
06 Feb 2018
How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation
Menaka Narayanan
Emily Chen
Jeffrey He
Been Kim
S. Gershman
Finale Doshi-Velez
FAtt
XAI
108
244
0
02 Feb 2018
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
Mike Wu
M. C. Hughes
S. Parbhoo
Maurizio Zazzi
Volker Roth
Finale Doshi-Velez
AI4CE
130
283
0
16 Nov 2017
Understanding Hidden Memories of Recurrent Neural Networks
Yao Ming
Shaozu Cao
Ruixiang Zhang
Zerui Li
Yuanzhe Chen
Yangqiu Song
Huamin Qu
HAI
40
201
0
30 Oct 2017
Deep and Confident Prediction for Time Series at Uber
Lingxue Zhu
N. Laptev
BDL
AI4TS
166
345
0
06 Sep 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences
Tim Miller
XAI
254
4,281
0
22 Jun 2017
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,871
0
14 Jun 2017
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
803
132,454
0
12 Jun 2017
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
219
2,910
0
14 Mar 2017
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
193
6,024
0
04 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
410
3,820
0
28 Feb 2017
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism
Edward Choi
M. T. Bahadori
Joshua A. Kulas
A. Schuetz
Walter F. Stewart
Jimeng Sun
AI4TS
123
1,249
0
19 Aug 2016
The Mythos of Model Interpretability
Zachary Chase Lipton
FaML
183
3,708
0
10 Jun 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
SILM
AAML
116
1,742
0
24 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
1.2K
17,071
0
16 Feb 2016
Distilling Knowledge from Deep Networks with Applications to Healthcare Domain
Zhengping Che
S. Purushotham
R. Khemani
Yan Liu
59
139
0
11 Dec 2015
Understanding Neural Networks Through Deep Visualization
J. Yosinski
Jeff Clune
Anh Totti Nguyen
Thomas J. Fuchs
Hod Lipson
FAtt
AI4CE
126
1,875
0
22 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
863
9,353
0
06 Jun 2015
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
367
19,745
0
09 Mar 2015
Supersparse Linear Integer Models for Optimized Medical Scoring Systems
Berk Ustun
Cynthia Rudin
130
354
0
15 Feb 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Ke Xu
Jimmy Ba
Ryan Kiros
Kyunghyun Cho
Aaron Courville
Ruslan Salakhutdinov
R. Zemel
Yoshua Bengio
DiffM
350
10,083
0
10 Feb 2015
Falling Rule Lists
Fulton Wang
Cynthia Rudin
66
258
0
21 Nov 2014
1