Synthetic data trained open-source language models are feasible alternatives to proprietary models for radiology reporting
Crossref DOI link: https://doi.org/10.1038/s41746-025-01658-3
Published Online: 2025-07-23
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Pandita, Aakriti
Keniston, Angela
Madhuripan, Nikhil
Text and Data Mining valid from 2025-07-23
Version of Record valid from 2025-07-23
Article History
Received: 17 August 2024
Accepted: 17 April 2025
First Online: 23 July 2025
Competing interests
: The authors (AP, AK, NM) declare no competing interests.