Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{172595,
        author = {Gajalakshmi S and Nalini M and Sridevi M and Meenakshi S},
        title = {ANDROID APPLICATION FOR DIABETES PREDICT ION USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {269-275},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172595},
        abstract = {Diabetes can be a reason for reducing life expectancy & quality. Predicting the chronic disorder is a fast growing global problem Earlier can reduce the risk and Complications of many diseases. It requires a proper active monitoring by using various smartphones sensors, smart watches etc. It is estimated that in 2010 there were globally 285 million people are suffering from this disease. The number is estimate in 2021 to be 536.6 million people it will rise to 783.2 million in 2045 in the absence of better control. These kind of prediction for all these different disease can be cured in proper manner. In this paper, an automatic diabetes prediction system using the support vector machine algorithm has been proposed, we are combining the work of our machine learning with the various logical techniques to bring forth the better results. Machine learning algorithms called support vector machines (SVM) are widely used for diabetes prediction.},
        keywords = {glucose level , sensors , risk , retinography , diabetes ,insulin ,pancreatic-beta , cells , accuracy},
        month = {January},
        }