This paper is in the following e-collection/theme issue:

Health Services Research (559) Natural Language Processing (921) Artificial Intelligence (2150) Electronic Health Records (1324) Ambient AI Scribes and AI-Driven Documentation Technologies (10) Ophthalmology (68)

Published on in Vol 14 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72894, first published .
Streamlining Ophthalmic Documentation With Anonymized, Fine-Tuned Language Models: Feasibility Study

Streamlining Ophthalmic Documentation With Anonymized, Fine-Tuned Language Models: Feasibility Study

Streamlining Ophthalmic Documentation With Anonymized, Fine-Tuned Language Models: Feasibility Study

Authors of this article:

Sebastian Arens1 Author Orcid Image ;   Quang Vinh Ngo1 Author Orcid Image ;   Anna Richling1 Author Orcid Image ;   Lucas Stürzbecher1 Author Orcid Image ;   Daniel Böhringer1 Author Orcid Image ;   Thomas Reinhard1 Author Orcid Image ;   Felix Heilmeyer2 Author Orcid Image
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