International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024
p-ISSN: 2395-0072
www.irjet.net
Vitamin Deficiency and Food Recommendation System Using Machine Learning B. Jhahnavi1, Uma shankar2, Chinmay Venkatesh3, Bhimineni Sai Teja4 1,2,3,4 Students, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India
---------------------------------------------------------------------***--------------------------------------------------------------------and nourishments based on people's characteristics and Abstract - Vitamin lack may be a major open well-being issue that influences billions of individuals worldwide.
inclinations.
In this paper, we display a machine learning approach for foreseeing vitamins and mineral insufficiency employing an engineered dataset of 5000 records with 10 attributes.
A Machine Learning-based show for anticipating the hazard of Sort 2 Diabetes mellitus (P2DM) based on components such as Age, Sex, Family History, Smoking Status, Physical Movement, and Dietary Propensities was created in a ponder called Khalid et al., (2021). The show was based on machine learning calculations, such as logistic regression, Decision tree, and Random Forest Classifier.
Different machine learning calculations such as Naïve Bayes, logistic regression, support vector machine, decision tree classifier, random forest classifier, and K-nearest neighbor classifier were utilized to anticipate vitamin and mineral lacks.
A moment thinks about (Zhang et al., 2020) utilized a cross breed demonstrate (collaborative sifting + substance-based sifting) to form a personalized count calories suggestion framework. The framework employments machine learning calculations (K-nearest Neighbor and Cosine similitude) to expect client inclinations and convey personalized eat less plans based on user's dietary propensities and dietary necessities.
In expansion, we created a web application to suggest food recommendations based on predicted vitamin deficiencies. The web application takes into consideration age, gender, height, weight, vitamin deficiency, dietary preferences, activity level, allergies, causes to predict the probability of diverse vitamin deficiencies.
1.INTRODUCTION
In any case, there is small investigate on how to form a comprehensive framework that takes under consideration diverse components such as age and sex, height and weight, vitamin deficiencies, dietary preferences, activity level, allergies, causes. The objective of this think about is to form a framework that combines machine learning calculations with user-provided information and gives personalized food suggestions.
Inadequate and unbalanced diet and lifestyle can lead to a variety of health problems, from obesity and diabetes to heart disease and cancer. The World Health Organization (WHO) reports that an unbalanced diet can lead to 14% of deaths due to gastrointestinal cancer, 11% from ICH (ischemic heart disease) and 9% from heart disease around the world. Millions of kids and adults also suffer from vitamin and mineral deficiency.
1.2 OBJECTIVE
To provide nutritional recommendations based on user information and preferences, we developed a web page that predicts food based on predicted health conditions. The web page takes user information as input along with the vitamin deficiency and recommends food rich in deficient nutrients using machine learning techniques.
The central goal of this project is to design, implement and assess the vitamin deficiency prediction and food recommendation system powered by machine learning algorithms. MODULES:
In this study, we focus on the potential for machine learning algorithms to predict vitamin deficiency. Our approach is even more practical by creating a web-based page that recommends foods based on a predicted health condition. More in-depth research using real-world data is needed to confirm our findings.
Data Collection
1.1 LITERATURE SURVEY
Data was collected for a study to predict vitamin deficiency and make food recommendations based on various attributes, including age, gender, height, weight, vitamin
Later ponders have illustrated that machine learning can be utilized to foresee wellbeing conditions and prescribe
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Data collection Data Mapping (noise reduction) Testing training ML algorithms Deficiency prediction
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