Diet Recommendation System for Human Health Using Machine Learning

In the past and present generation, the change in lifestyle of young people, less number of physical activities and eating fast food led to an alarming increase of diseases especially with college students. The unhealthy diet of students is responsible for unbalanced weight. The body mass index is used to classify a person's mass or weight as underweight, normal weight, over weight and obese based on tissue mass (bone, fat, and muscle) and height. Underweight leads to malnutrition, vitamin deficiencies, decrease in immune system function, growth issues and development issues. Major risk of being overweight leads to type-2 diabetes. Machine learning algorithms can solve many health problems. The project suggests the creation of an electronic college nurse that can perform the same functions as a human college nurse. This e-nurse will track students' health by utilizing BMI measurements, identify health issues like Type-2 diabetes by utilizing machine learning algorithms, and create a customized e-learning program that focuses on healthy habits such as regular exercise and a nutritious diet. These e-learning modules will be incorporated at appropriate intervals during the students' academic journey.