Diabetes mellitus'in erken tespit ve sınıflandırılması için transfer öğrenme tabanlı bir çerçevenin geliştirilmesi ve değerlendirilmesi: Tıbbi görüntüleme ve biyokimyasal veriler üzerinde

Diabetes mellitus, a complex metabolic disorder characterized by elevated blood glucose levels, has emerged as a global healthcare crisis of unprecedented magnitude. With its relentless increase in prevalence and the profound impact it exerts on individuals, healthcare systems, and societies worldwide, diabetes mellitus presents a multifaceted challenge that demands innovative and transformative solutions, this research seeks to enhance healthcare outcomes by contributing to a more efficient and effective diagnostic process for this chronic metabolic disorder. The overarching objective of this thesis is to pioneer the development and evaluation of a transfer learning-based framework designed explicitly for early detection and accurate classification of diabetes mellitus through the integration of medical imaging and biochemical data.