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Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations

Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations

10 May 2025
Dima Alattal
Asal Khoshravan Azar
P. Myles
Richard Branson
Hatim Abdulhussein
Allan Tucker
ArXiv (abs)PDFHTML

Papers citing "Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations"

13 / 13 papers shown
Title
Stop ordering machine learning algorithms by their explainability! A
  user-centered investigation of performance and explainability
Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability
L. Herm
Kai Heinrich
Jonas Wanner
Christian Janiesch
33
87
0
20 Jun 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
Satyapriya Krishna
Tessa Han
Alex Gu
Steven Wu
S. Jabbari
Himabindu Lakkaraju
246
195
0
03 Feb 2022
Deep Neural Networks and Tabular Data: A Survey
Deep Neural Networks and Tabular Data: A Survey
V. Borisov
Tobias Leemann
Kathrin Seßler
Johannes Haug
Martin Pawelczyk
Gjergji Kasneci
LMTD
112
696
0
05 Oct 2021
The Role of Explainability in Assuring Safety of Machine Learning in
  Healthcare
The Role of Explainability in Assuring Safety of Machine Learning in Healthcare
Yan Jia
John McDermid
T. Lawton
Ibrahim Habli
73
48
0
01 Sep 2021
Tabular Data: Deep Learning is Not All You Need
Tabular Data: Deep Learning is Not All You Need
Ravid Shwartz-Ziv
Amitai Armon
LMTD
159
1,275
0
06 Jun 2021
Unbox the Black-box for the Medical Explainable AI via Multi-modal and
  Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond
Guang Yang
Qinghao Ye
Jun Xia
132
501
0
03 Feb 2021
Counterfactual Explanations and Algorithmic Recourses for Machine
  Learning: A Review
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Sahil Verma
Varich Boonsanong
Minh Hoang
Keegan E. Hines
John P. Dickerson
Chirag Shah
CML
145
173
0
20 Oct 2020
Interpretable Machine Learning for COVID-19: An Empirical Study on
  Severity Prediction Task
Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task
Han-Ching Wu
Wenjie Ruan
Jiangtao Wang
Dingchang Zheng
Bei Liu
...
Xiangfei Chai
Jian Chen
Kunwei Li
Shaolin Li
A. Helal
41
26
0
30 Sep 2020
Interpretability of machine learning based prediction models in
  healthcare
Interpretability of machine learning based prediction models in healthcare
Gregor Stiglic
Primož Kocbek
Nino Fijačko
Marinka Zitnik
K. Verbert
Leona Cilar
AI4CE
65
386
0
20 Feb 2020
Explanation in Artificial Intelligence: Insights from the Social
  Sciences
Explanation in Artificial Intelligence: Insights from the Social Sciences
Tim Miller
XAI
252
4,273
0
22 Jun 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
22,018
0
22 May 2017
Model-Agnostic Interpretability of Machine Learning
Model-Agnostic Interpretability of Machine Learning
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
86
839
0
16 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
FAttFaML
1.2K
17,033
0
16 Feb 2016
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