Research Information System
ACM Transactions on Asian and Low-Resource Language Information Processing, no.10, pp.1-13, 2025 (SCI-Expanded)
The development of a Turkish-speciic Large Language Model (LLM) for healthcare presents a unique opportunity to enhance AI’s accessibility and relevance for Turkish-speaking medical practitioners and patients. This study introduces a specialized Turkish Medical LLM ine-tuned on over 167,732 real patient-doctor question-answer pairs sourced from a trusted medical platform and capturing authentic linguistics in Turkish medical language. Utilizing models like LLAMA 3, the ine-tuning process was supported by Low-Rank Adaptation (LoRA) and involved innovative methods to mitigate catastrophic forgetting, including spherical linear interpolation (Slerp) merging. Evaluation of the model’s performance through similarity scores, GPT-3.5 assessments, and expert reviews indicates signiicant improvement in the model’s ability to generate medically accurate responses. This Turkish Medical LLM demonstrates potential to support medical decision-making and patient interaction in Turkish healthcare settings, ofering an essential resource for enhancing AI inclusivity across languages.