Sources of bias in artificial intelligence that perpetuate healthcare disparities-A global review.

Background: While artificial intelligence (AI) offers possibilities of advanced clinical prediction and decision-making in healthcare, models trained on relatively homogeneous datasets, and populations poorly-representative of underlying diversity, limits generalisability and risks biased AI-based decisions. Here, we describe the landscape of AI in clinical medicine to delineate population and data-source disparities.

Methods: We performed a scoping review of clinical papers published in PubMed in 2019 using AI techniques.