Bibliometric analysis maps ethical hotspots in ophthalmic AI deployments


 Artificial intelligence is rapidly transforming ophthalmology, but a new bibliometric analysis warns that ethical frameworks are lagging behind technical progress. The study maps the landscape of AI research in eye care, highlighting critical gaps in how issues like data privacy, transparency, and accountability are addressed. While AI models trained on retinal images offer diagnostic breakthroughs, they also pose risks of patient re-identification and algorithmic bias. 

The study calls for stronger global collaboration to establish clear ethical guidelines, arguing that laws like GDPR and HIPAA must be supplemented by specific frameworks that ensure trust and fairness in clinical AI deployments.

Read the original article at: https://www.nature.com/articles/s41746-025-01976-6


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