Artificial intelligence has exposed pernicious bias within health data that constitutes
substantial ethical threat to the use of machine learning in medicine. 1, 2 Solutions of …

INTRODUCTION Machine learning for healthcare (MLHC) is at the juncture of leaping from
the pages of journals and conference proceedings to clinical implementation at the bedside …

The problem of algorithmic bias represents an ethical threat to the fair treatment of patients
when their care involves machine learning (ML) models informing clinical decision-making …

To the Editor—As of June 2022, a wide range of Artificial Intelligence (AI) as a Medical
Device (AIaMDs) have received regulatory clearance internationally, with at least 343 …

Artificial Intelligence has been applied in academic research and in inference tasks across
the broader economy with demonstrable success, 1 but less so for the core functions of …

Machine learning is used increasingly in clinical care to improve diagnosis, treatment
selection, and health system efficiency. Because machine-learning models learn from …

Data and data-driven technologies are playing an increasingly influential role in health care,
helping to detect disease earlier, move care closer to home, encourage health-promoting …

Machine learning in medicine: Addressing ethical challenges | PLOS Medicine Skip to main
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The use of machine learning to guide clinical decision making has the potential to worsen
existing health disparities. Several recent works frame the problem as that of algorithmic …

Treating health disparities with artificial intelligence | Nature Medicine Skip to main content
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