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Concept-based model explanations for Electronic Health Records

Concept-based model explanations for Electronic Health Records

3 December 2020
Diana Mincu
Eric Loreaux
Shaobo Hou
Sebastien Baur
Ivan V. Protsyuk
Martin G. Seneviratne
A. Mottram
Nenad Tomašev
Alan Karthikesanlingam
Jessica Schrouff
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Papers citing "Concept-based model explanations for Electronic Health Records"

14 / 14 papers shown
Title
C-SHAP for time series: An approach to high-level temporal explanations
C-SHAP for time series: An approach to high-level temporal explanations
Annemarie Jutte
Faizan Ahmed
Jeroen Linssen
Maurice van Keulen
AI4TS
33
0
0
15 Apr 2025
A Self-explaining Neural Architecture for Generalizable Concept Learning
A Self-explaining Neural Architecture for Generalizable Concept Learning
Sanchit Sinha
Guangzhi Xiong
Aidong Zhang
43
2
0
01 May 2024
Explaining Deep Neural Networks for Bearing Fault Detection with
  Vibration Concepts
Explaining Deep Neural Networks for Bearing Fault Detection with Vibration Concepts
Thomas Decker
Michael Lebacher
Volker Tresp
FAtt
26
2
0
17 Oct 2023
A Unified Concept-Based System for Local, Global, and Misclassification
  Explanations
A Unified Concept-Based System for Local, Global, and Misclassification Explanations
Fatemeh Aghaeipoor
D. Asgarian
Mohammad Sabokrou
FAtt
27
0
0
06 Jun 2023
Explainable AI for Time Series via Virtual Inspection Layers
Explainable AI for Time Series via Virtual Inspection Layers
Johanna Vielhaben
Sebastian Lapuschkin
G. Montavon
Wojciech Samek
XAI
AI4TS
34
26
0
11 Mar 2023
Mapping Knowledge Representations to Concepts: A Review and New
  Perspectives
Mapping Knowledge Representations to Concepts: A Review and New Perspectives
Lars Holmberg
P. Davidsson
Per Linde
34
1
0
31 Dec 2022
Concept Activation Regions: A Generalized Framework For Concept-Based
  Explanations
Concept Activation Regions: A Generalized Framework For Concept-Based Explanations
Jonathan Crabbé
M. Schaar
59
46
0
22 Sep 2022
Towards Benchmarking Explainable Artificial Intelligence Methods
Towards Benchmarking Explainable Artificial Intelligence Methods
Lars Holmberg
11
4
0
25 Aug 2022
Boosting the interpretability of clinical risk scores with intervention
  predictions
Boosting the interpretability of clinical risk scores with intervention predictions
Eric Loreaux
Ke Yu
Jonas Kemp
Martin G. Seneviratne
Christina W. Chen
...
Ivan V. Protsyuk
Natalie Harris
Alexander DÁmour
Steve Yadlowsky
Ming-Jun Chen
19
1
0
06 Jul 2022
Human-Centered Concept Explanations for Neural Networks
Human-Centered Concept Explanations for Neural Networks
Chih-Kuan Yeh
Been Kim
Pradeep Ravikumar
FAtt
42
26
0
25 Feb 2022
Acquisition of Chess Knowledge in AlphaZero
Acquisition of Chess Knowledge in AlphaZero
Thomas McGrath
A. Kapishnikov
Nenad Tomašev
Adam Pearce
Demis Hassabis
Been Kim
Ulrich Paquet
Vladimir Kramnik
36
159
0
17 Nov 2021
Making Corgis Important for Honeycomb Classification: Adversarial
  Attacks on Concept-based Explainability Tools
Making Corgis Important for Honeycomb Classification: Adversarial Attacks on Concept-based Explainability Tools
Davis Brown
Henry Kvinge
AAML
45
7
0
14 Oct 2021
Self-explaining Neural Network with Concept-based Explanations for ICU
  Mortality Prediction
Self-explaining Neural Network with Concept-based Explanations for ICU Mortality Prediction
Sayantan Kumar
Sean C. Yu
Thomas Kannampallil
Zachary B. Abrams
Andrew Michelson
Philip R. O. Payne
FAtt
19
7
0
09 Oct 2021
Best of both worlds: local and global explanations with
  human-understandable concepts
Best of both worlds: local and global explanations with human-understandable concepts
Jessica Schrouff
Sebastien Baur
Shaobo Hou
Diana Mincu
Eric Loreaux
Ralph Blanes
James Wexler
Alan Karthikesalingam
Been Kim
FAtt
34
28
0
16 Jun 2021
1