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@article{188828,
        author = {SOUMYABRATA SAMANTA and SUCHETAN SARKAR and ROHIT DEY and SAYAN SINGHA ROY and MD.MIKAIL AZAM and SUMIT PAL and SALMAN KHAN and ROHIT SK},
        title = {Artificial Intelligence-Driven Therapeutic Strategies for Type 3 Diabetes: A New Frontier in Neuro-Metabolic Medicine},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {3481-3505},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188828},
        abstract = {Type 3 Diabetes, often described as diabetes of the brain, represents a pathological state characterized by impaired insulin signalling, glucose hypometabolism, neuroinflammation, and progressive cognitive decline. Recent advancements in artificial intelligence (AI) have opened transformative opportunities for understanding and treating this complex neuro-metabolic disorder. AI-driven neuroimaging analytics enable early detection of cerebral insulin resistance by identifying subtle alterations in hippocampal structure, amyloid-beta deposition, and metabolic deficits long before clinical symptoms emerge. Machine learning models further enhance diagnostic precision by integrating multimodal biomarkers, including genetic variants, inflammatory markers, and cerebrospinal fluid signatures, to stratify high-risk populations and predict disease progression. In therapeutic development, deep learning accelerates the discovery of novel drug candidates targeting insulin receptor pathways, amyloid aggregation, tau phosphorylation, and mitochondrial dysfunction. AI-guided personalized medicine frameworks support individualized treatment by combining patient-specific imaging, metabolic status, and genomic data to optimize use of insulin sensitizers, GLP-1 agonists, and neuroprotective agents. Moreover, AI-driven optimization of brain-targeted insulin delivery systems—such as nanocarriers and intranasal formulations—improves blood–brain barrier penetration and dose precision. Digital health tools powered by AI enable continuous cognitive monitoring through speech analysis, gait tracking, and behavioral pattern recognition, facilitating early intervention. Additionally, AI-enhanced neuromodulation platforms refine parameters for techniques like deep brain stimulation (DBS) and transcranial magnetic stimulation (TMS), aiming to restore insulin responsiveness and synaptic function ai offers a multidimensional framework for early diagnosis, precision therapeutics, and continuous monitoring of Type 3 Diabetes, marking a critical advancement in combating Alzheimer’s-related metabolic impairment.},
        keywords = {Diabetes, Pathological, Hypometabolism, Neuroinflammation, Neuroprotective},
        month = {December},
        }