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@article{172567,
        author = {Abinaya V and Chitra.K},
        title = {DIABETIC PREDICTION USING SOFT COMPUTING TECHNIQUES- A REVIEW OF THE LITERATURE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {337-340},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172567},
        abstract = {Diabetes, especially Type 2 Diabetes Mellitus
(T2DM), has become a significant global health
challenge, with an increasing number of cases every
year. Early prediction and diagnosis of diabetes are
crucial for effective management, as they enable
timely intervention to prevent complications. In
recent years, the application of soft computing
techniques for diabetic prediction has gained
considerable attention due to their ability to handle
uncertainties, non-linearity, and complex patterns
within data. This literature review explores the
various soft computing approaches employed in
diabetic prediction, focusing on methods such as
neural networks, fuzzy logic, genetic algorithms, and
hybrid systems},
        keywords = {},
        month = {February},
        }