The medical algorithmic audit
Artificial intelligence systems for health care, like any other medical device, have the potential to fail. However, specific qualities of artificial intelligence systems, such as the tendency to learn spurious correlates in training data, poor generalisability to new deployment settings, and a paucity of reliable explainability mechanisms, mean they can yield unpredictable errors that might be entirely missed without proactive investigation. We propose a medical algorithmic audit framework that
Record details
Published: 5 April 2022
Source: OpenAlex
Category: Research
Topics: Healthcare · Transparency · Finance, VC & PE
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (5 April 2022), “The medical algorithmic audit,” evidence record 9240, https://ethics.ai/record/9240 (originally published by OpenAlex).
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