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...
Muhammad Jamil, A. Kavak, S. Omurca et al.· Diagnostics· 0 citations
A confidence-aware hybrid vision–language framework engineered for traditional Turkish food recognition and structured nutritional assessment that demonstrates localized plate detection, adaptive portion analysis, and structured nutrient tracking, providing a scalable design for consumer-facing digital nutrition platfo...
Furkan Göz, Muhammad Jamil, A. Kavak et al.· Nutrients· 0 citations
The proposed Retrieval-Augmented Large Language Model architecture for trustworthy conversational AI in diabetes care is presented, which combines clinical entity recognition, hybrid dense–sparse retrieval, patient-context filtering, cross-encoder reranking, evidence-constrained prompt construction, and multi-layer saf...
Muhammad Jamil, A. Kavak, Sema Bayraktar et al.· IEEE Access· 0 citations
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