Evaluating trustworthiness in AI-Based diabetic retinopathy screening: addressing transparency, consent, and privacy challenges
Ensuring trustworthy AI requires transparent and accountable data practices, robust patient consent mechanisms, and regulatory frameworks aligned with ethical and privacy standards. Addressing these issues is vital to safeguarding patient rights, preventing data misuse, and fostering responsible AI ecosystems in the Global South.
Authors
- Karthik Adapa (ORCID: https://orcid.org/0000-0002-3970-588X)
- Harsh Rastogi (ORCID: https://orcid.org/0009-0002-1568-4321)
- Debarati Sarkar
- Mona Duggal (ORCID: https://orcid.org/0000-0002-9404-2871)
- Garima Singh Verma
- Anshul Chauhan (ORCID: https://orcid.org/0000-0002-2434-935X)
Institutions
- University of North Carolina Health Care (US)
- Indian Institute of Technology Jodhpur (IN)
- Indian Council of Medical Research (IN)
- National Institute of Medical Statistics (IN)
- Post Graduate Institute of Medical Education and Research (IN)
Publication Details
- Journal
- BMC Medical Ethics
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1186/s12910-025-01265-7
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00