The value of standards for health datasets in artificial intelligence-based applications.

ABSTRACT: Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in research and inequalities of access. This study aims to explore existing standards, frameworks and best practices for ensuring adequate data diversity in health datasets. Exploring the body of existing literature and expert views is an important step towards the development of consensus-based guidelines. The study comprises two parts: a systematic review of existing standards, frameworks and best pra

SUBMITTER: Arora A 

PROVIDER: S-EPMC10667100 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature