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

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
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article

AI-Powered Health Prediction and Wellness Promotion Through Grocery Purchase Analysis

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare
article

AI-Powered Health Prediction and Wellness Promotion Through Grocery Purchase Analysis

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Anna University, Chennai (IN)
Openalex Percentile: Top 49%
Artificial Intelligence in Healthcare
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AI-Powered Health Prediction and Wellness Promotion Through Grocery Purchase Analysis · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS