Stanisław Deniziak

Enhancing clinical reasoning and diagnostic precision through scaling laws and multi-stage supervised fine-tuning in open-weight medical large language models

Abstract The emergence of large language models offers unprecedented opportunities to transform clinical workflows. However, reliance on proprietary closed-source models poses significant risks to data privacy, institutional autonomy, and reasoning transparency. This study invest...