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May 18, 2023 � In this work, we examine three challenges using experiments with electronic health record data: computational feasibility, choosing between methods, and�...
Feature importance is often used to explain clinical prediction models. In this work, we examine three challenges using experiments with electronic health�...
This work aims to create awareness of the disagreement between feature importance methods and underscores the need for guidance to practitioners how to deal�...
The Virtual Health Library is a collection of scientific and technical information sources in health organized, and stored in electronic format in the�...
Challenges of estimating global feature importance in real-world health care data Har passerat � F�rel�sare � Aniek Markus F�rel�sare.
Feb 3, 2020 � The use of RWD to identify treatment effect modifiers can help guide patient selection (e.g., picking the patients most likely to respond to�...
Missing: Feature | Show results with:Feature
This article aims to identify the barriers to the acceptance of NRS and steps that may facilitate increases in the acceptability of NRS in the future.
Jun 24, 2021 � In this review article, we provide a summary overview of the challenges and risks regarding the use of RWD and its translation into real-world evidence.
Jan 5, 2023 � Biases in data and other underlying quality issues, for example, can be hard to detect and could limit the insights derived from such data.
Missing: Global | Show results with:Global
We propose a new procedure for computing global feature importance that involves aggregating local counterfactual explanations.