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@article{170756,
        author = {MS KOMAL SURESH AGE and Mr Sanket Sanjay Amrutkar and Mr Kalpesh Rajendra Gawale and Ms Harshada Rajendra Gavale and Mrs Shilpa Amit Shinde and Mr Bhagat Suraj Dilip},
        title = {MERGING BIOMARKERS FOR EARLY DETECTION OF TYPE 2 DIABETES},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {149-153},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170756},
        abstract = {Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder with a rising global burden, necessitating timely and effective detection strategies. Biomarkers have emerged as powerful tools for early diagnosis, aiding in identifying high-risk individuals and improving disease management. This review explores the integration of diverse biomarkers, including genetic, proteomic, metabolic, and inflammatory indicators, to enhance early T2DM detection. Emphasis is placed on their mechanistic roles, diagnostic accuracy, and predictive capabilities. Advanced analytical approaches, such as multi-omics platforms and machine learning, are discussed as critical enablers for merging biomarkers into comprehensive diagnostic models. The integration of these biomarkers offers a promising pathway toward personalized medicine, enabling proactive interventions and reducing the progression of diabetes-related complications. Future research priorities include large-scale validation studies, standardization of biomarker assays, and bridging gaps in clinical translation to achieve a reliable, early diagnostic framework for T2DM.},
        keywords = {Type 2 Diabetes (T2D), Biomarkers, Early Detection, Predictive Biomarkers Glycemic Control, Insulin Resistance, Glucose Homeostasis},
        month = {December},
        }