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@article{172184,
        author = {Siddhant Chavan and Anisha Kumari and Tilakraj R Revankar and Poorvika. P and Dr. Shanmugarathinam and Dr.Abdul Khadar A},
        title = {Health Buddy},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {2182-2187},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172184},
        abstract = {In a fast-paced modern world, maintaining optimal health through proper nutrition and hydration is often neglected. This paper introduces Health Buddy, a comprehensive application designed to address these challenges. The app employs a trained machine learning model to analyze users’ dietary inputs, predict nutritional content (vitamins, proteins, and calories), and track physical activities and hydration. Over time, it identifies potential nutrient deficiencies and suggests ways to mitigate them, preventing health risks associated with imbalances. Health Buddy also integrates habit-forming techniques, reminders, and data visualization to encourage consistent health management. This study discusses the app’s methodology, features, implementation, and the potential impact on personalized healthcare.},
        keywords = {},
        month = {January},
        }