The myth of generalisability in clinical research and machine learning in health care

Abstract

An emphasis on overly broad notions of generalisability as it pertains to applications of machine learning in health care can overlook situations in which machine learning might provide clinical utility. We believe that this narrow focus on generalisability should be replaced with wider considerations for the ultimate goal of building machine learning systems that are useful at the bedside.

Cited by papers we hold 5

• Evaluation of clinical prediction models (part 1): from development to external validation · 2024
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• There is no such thing as a validated prediction model · 2023
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• Ethics for Artificial Intelligence: Focus on the Use of Radiology Images · 2022
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• Sources of bias in artificial intelligence that perpetuate healthcare disparities—A global review · 2022
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• Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare · 2022
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