Gradient Descent-Based Optimization for Personalized Nutritional Needs and Health/Activity Goals

Precision Nutrition (PN) represents a personalized approach to dietary planning that considers genetic factors, body measurements, metabolism, lifestyle, and health goals. This study proposes the use of gradient descent optimization algorithms to determine personalized macronutrient quantities (protein, carbs, and fat) for each meal, factoring in individual characteristics. The primary goal is to create a technical tool that enhances individuals ability to achieve health objectives. The study comprises two phases: algorithm development and testing with diverse participants. The results will evaluate the algorithms effectiveness and guide future research. This research has the potential to advance precision nutrition by providing efficient tools for personalized dietary planning, offering valuable insights into the relationship between individual traits and dietary needs in a personalized way.