Browsing by Author "Thilakarathne, P.R.H.N.G."

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    Integrating Large Language Models into Personalized Diabetes Care: A Systematic Review of Clinical Applications, Model Adaptation Strategies, and Ethical Implications
    (Faculty of Engineering, 2025-09-09) Jayakody,J.A.U.S.; Jayawardhana, S.M.M.S.; Thilakarathne, P.R.H.N.G.
    This systematic review examines the integration of Large Language Models (LLMs) into personalized diabetes care, focusing on clinical applications, adaptation strategies, and ethical considerations. As diabetes management demands increasingly personalized approaches, LLMs including GPT-3 and GPT-4 show promise for patient education, clinical decision support, and diagnostic assistance. This review synthesizes findings from studies published between 2018 and 2025 to evaluate LLM clinical applications and assess adaptation techniques. Key applications include conversational agents for patient education, personalized decision-making systems, and predictive modeling for diabetes-related complications. Model adaptation through domain-specific training and multimodal integration demonstrates enhanced performance in clinical settings. However, significant challenges persist, including data privacy concerns, model fairness issues, and limited real-world validation. Ethical considerations encompass training bias and data security, highlighting the need for privacy-preserving approaches. The review identifies critical gaps in current research and proposes future directions emphasizing explainable AI models to build trust among healthcare professionals and patients. While LLMs offer transformative potential for personalized diabetes care, their responsible integration requires addressing technical, ethical, and regulatory challenges. This synthesis provides a foundation for advancing LLM applications in diabetes management while ensuring patient safety and equitable care delivery.