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Article . 2023
License: CC BY
Data sources: Datacite
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Diet Recommendation System Using Machine Learning

Authors: Anamika K; Jobin T J;

Diet Recommendation System Using Machine Learning

Abstract

Abstract—In today's society, people are increasingly conscious about their health and lifestyle. However, simply avoiding unhealthy foods and exercising may not be sufficient for maintaining a balanced diet. To lead a healthy life, a balanced diet tailored to an individual's height, weight, and age is necessary. When coupled with physical activity, a proper diet can assist in achieving and sustaining a healthy weight, decreasing the risk of chronic diseases such as heart disease and cancer, and improving overall health. A balanced diet should provide the necessary nutrients for the body to function correctly. Food calories are a measure of the energy stored in food, which the body utilizes for various activities such as breathing, walking, and running. While the average person requires approximately 2000 calories daily, calorie intake is dependent on physical characteristics like weight, height, age, and gender. As a result, one's food choices impact not just their current wellbeing but also their future health. Therefore, a suggested diet plan based on one's physical characteristics and goals may be recommended by a diet recommendation system.

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Keywords

Diet Plan, Machine Learning, Calories, Recommendation System, Basic Metabolic Rate, Harris-Benedict equation, Body Mass Index

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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