Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques

Area of Science:

• Artificial Intelligence
• Health Informatics
• Nutritional Science

Background:

• Obesity is a critical global health issue, increasing the risk of major diseases like heart disease, stroke, diabetes, and cancer.
• Current obesity management relies on calorie information, but lacks personalization considering individual health status and physical activity.
• Effective obesity management requires a holistic approach beyond simple calorie counting.

Purpose of the Study:

• To develop an AI-based application utilizing a genetic algorithm (GA) for obesity management.
• To create a tool that tracks users' energy balance and predicts necessary calorie intake for weight management.
• To personalize meal predictions based on individual health data and nutritional requirements.

Main Methods:

• An AI application driven by a genetic algorithm (GA) was developed.
• The system integrates user-provided food preferences, health records (cholesterol, diabetes, physical activity), and nutrient databases.
• Micro- and macronutrient data were used for predicting suitable meals and daily calorie needs.

Main Results:

• The AI model successfully predicted glycemic and non-glycemic foods tailored to user conditions and nutritional needs.
• The system demonstrated effectiveness in tracking user weight loss progress, daily nutritional intake, and calorie consumption.
• Personalized meal predictions were generated to support health goals without compromising user well-being.

Conclusions:

• The AI-driven application offers a valuable tool for personalized obesity management.
• The system aids individuals, dieticians, and health professionals in making informed decisions for weight control.
• This technology can support educational initiatives in dietetics and consumer science for obesity-related health challenges.