Design and Evaluation of a Source-Grounded Medical LLM for Clinical Decision Support and Patient Care in Trustworthy Diagnostic Systems

Background/Objectives: Large language models (LLMs) are increasingly explored for clinical decision support and digital health applications. However, reliable diagnostic assistance remains challenging for low-resource medical languages such as Turkish due to limited source grounding, transparency, clinical safety, and localized medical knowledge. This study presents TurkishMedLLM, a source-grounded and safety-aware Turkish medical LLM designed for clinician-supervised diagnostic decision support, symptom interpretation, and patient care.