Artificial intelligence in predicting diseases from food consumption

Abstract

The increasing prevalence of dietary-related health issues has necessitated the development of tools to analyze food consumption and its impact on health. This project explores the potential of artificial intelligence (AI) in predicting diseases based on food consumption patterns.Utilizing a dataset encompassing various food categories—such as fruits, dairy, and grains—we analyze the nutritional components, including vitamins and enzymes, in each food item. By identifying overconsumption patterns, our model predicts potential diseases linked to these imbalances. The methodology involves data preprocessing, API integration for real-time data fetching, and applying machine learning (ML) algorithms to derive insights. The ultimate goal is to empower individuals with personalized dietary recommendations and contribute to preventive healthcare.