Evaluating trustworthiness in AI-Based diabetic retinopathy screening: addressing transparency, consent, and privacy challenges.

ABSTRACT:

Background

Artificial intelligence (AI) offers significant potential to drive advancements in healthcare; however, the development and implementation of AI models present complex ethical, legal, social, and technical challenges, as data practices often undermine regulatory frameworks in various regions worldwide. This study explores stakeholder perspectives on the development and deployment of AI algorithms for diabetic retinopathy (DR) screening, with a focus on ethical risks, data practices, governance, and emerging shortcomings in the Global South AI discourse.

Methods

Fifteen semi-structured interviews were conducted with ophthalmologists, program officers, AI developers, bioethics experts, and legal professionals. Thematic analysis was guided by OECD principles for resp

SUBMITTER: Chauhan A 

PROVIDER: S-EPMC12532412 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature