AI-Powered Health Prediction and Wellness Promotion Through Grocery Purchase Analysis
This article presents an innovative AI-driven system that leverages grocery purchase data to predict health risks and promote wellness through targeted campaigns. The system employs advanced machine learning techniques, including deep neural networks and natural language processing, to analyze receipt data and generate personalized health insights. By integrating data collection, deep learning analysis, health risk prediction, and targeted campaign generation, the system aims to bridge the gap between consumer behavior and proactive health management. The article explores the technical implementation of the system, discusses ethical considerations surrounding data privacy and algorithmic bias, and outlines potential future directions for development, including integration with wearable devices and collaboration with healthcare providers.
Institutions
- Anna University, Chennai (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-07-12
- DOI
- https://doi.org/10.5281/zenodo.15870054
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00