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@article{207145,
        author = {A Surekha and K Reshma Reddy},
        title = {Artificial Intelligence and Precision Nutrition in Type 2 Diabetes - Associated Reproductive Dysfunction},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {4297-4308},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207145},
        abstract = {Type 2 diabetes mellitus (T2DM) is a major metabolic disorder that not only affects glucose regulation but also contributes to reproductive dysfunction in both men and women. Insulin resistance, chronic inflammation, oxidative stress, hormonal imbalance, and mitochondrial dysfunction associated with T2DM can negatively impact gonadal function, gamete quality, fertility potential, and pregnancy outcomes. Nutritional management plays a crucial role in improving metabolic and reproductive health; however, conventional dietary approaches often lack personalization and long-term adherence support.
Recent advances in artificial intelligence (AI) and machine learning (ML) are transforming precision nutrition and diabetes care through individualized, data-driven strategies. AI-based technologies, including image- and sensor-assisted dietary assessment, glycemic response prediction, personalized meal planning, and metabolic monitoring, enable the integration of clinical, nutritional, and lifestyle data to optimize patient-specific interventions. In reproductive medicine, AI applications are also being explored for fertility prediction, reproductive health assessment, and assisted reproductive analytics, offering new opportunities for improving reproductive outcomes in individuals with T2DM.
Dietary approaches such as low-glycemic index diets, Mediterranean dietary patterns, plant-based nutrition, and insulin-sensitizing micronutrients including vitamin D and myo-inositol have demonstrated beneficial effects on glycemic control and reproductive parameters. The integration of AI with precision nutrition may further enhance dietary adherence, metabolic regulation, and personalized reproductive care.
This article discusses the relationship between T2DM, reproductive dysfunction, nutrition, and emerging AI-driven precision healthcare approaches, while also highlighting current challenges related to algorithmic bias, data privacy, clinical validation, and equitable healthcare access.},
        keywords = {Type 2 diabetes mellitus, reproductive health, precision nutrition, artificial intelligence, insulin resistance, fertility, machine learning, preconception care},
        month = {July},
        }