In this project, the objective is to predict whether the person has Diabetes or not based on various features like Number of Pregnancies, Insulin Level, Age, BMI.

Emory BMI GSoC Project Ideas

The completed code for the BMI Project - The Complete Flutter Development Bootcamp

Analysis workflow for MRC-IEU PhD mini-project on childhood BMI effect on breast cancer

machine learning model that predicts body mass index from face images

JavaScript Projects for beginners. Animation card, Analog clock, BMI calculator, Calculator, Countdown, Dynamic Calendar, Music player, Parallax website, Temperature converter, Todo list, Weather app, Weight converter.

This is an application that uses the Flutter framework, SQFLite as a database to record blood pressure, blood sugar, BMI, or create medication reminders in multi mobile platforms You can run this project on iOS, Android

BMI calculator app built in Android Studio using Java. A beginner friendly project with a clean UI and easy code implementation.

✨Machine Learning & Data Analysis project predicting BMI, Stress Level, and clustering health-related features using Python. Implements Regression, Classification (Logistic, KNN, Decision Tree, Random Forest, SVM, Naive Bayes), K-Means & Hierarchical Clustering, with visualizations in Matplotlib & Seaborn.

A single-page, responsive BMI (Body Mass Index) calculator built with plain HTML, CSS and JavaScript. Designed to default to dark mode, work well on both mobile and desktop, and include an inline SVG chart + radial gauge. Uses a PNG favicon placed at the project root.

Diabetes Prediction is my weekend practice project. In this I used KNN Neighbors Classifier to trained model that is used to predict the positive or negative result. Given set of inputs are BMI(Body Mass Index),BP(Blood Pressure),Glucose Level,Insulin Level based on this features it predict whether you have diabetes or not.

A simple and interactive web project where users can calculate their Body Mass Index (BMI) and take a fun health quiz based on their results. It promotes fitness awareness by providing instant feedback on both BMI status and healthy habits!

Calculate your BMI. Beginner me Flutter project

Kalkulator BMI Sederhana | Final Project RevoU Fundamental Course Software Engineering

A simple BMI calculator built with JavaScript for quick body mass index calculation. Helps users measure health category using height and weight inputs. Perfect for health apps, demo projects, and learning logic.

Emory BMI GSoC 2020 Project Ideas

This is BMI Calculator. You can calculate your BMI using this application. I developed this project using flutter.

BMI Project for the Biomedical Engineering Department at Imperial College London, UK

BMI Calculator Mini Project in .Net MAUI

This project is a simple Body Mass Index (BMI) calculator made using HTML, CSS, JavaScript and React.js.

☕ DummyBox is a Java project aimed at demonstrating object-oriented programming principles. It includes features such as creating profile cards, calculating age and zodiac signs, computing geometric shapes' areas, performing BMI calculations, and playing the dice game Craps. Visit the GitHub repository for more details and contributions.

The is a Web App project that helps the user to identify whether someone is suffering from diabetes by simply inputting certain values like BMI, Glucose level, Blood pressure etc. with the help of kaggle database.

Diabetes Prediction Project Using Machine Learning. This app is a simple web application using the Flask framework, where users can input health data (like glucose levels, BMI, etc.) to predict if they are diabetic or not based on a Logistic Regression model.

This project features an HTML scrape off of the UGA Football website (works as of 2022). The data consists of players, height, weight, hometown, and more. Throughout the data cleaning and transformation process, I appropriately deal with nulls, dups in a should-be-unique column, and string data that should be split into multiple columns. I create dictionaries, functions, and visualizations that help me understand the distribution and values of data. I finish it off with some visualizations that show BMI and weight class! I do not know anything about football or BMI, but I am able to show a story with my code and visuals.

Stroke is the second leading cause of death worldwide and remains an important health burden both for individuals and for the national healthcare systems. Potentially modifiable risk factors for stroke include hypertension, cardiac disease, diabetes, dysregulation of glucose metabolism, atrial fibrillation, and lifestyle factors. Therefore, the goal of our project is to apply principles of machine learning over large existing data sets to effectively predict stroke based on potentially modifiable risk factors. Then it intended to develop the application to provide a personalized warning based on each user’s level of stroke risk and a lifestyle correction message about the stroke risk factors. In this article, we discuss the symptoms and causes of a stroke and also a machine learning model that predicts the likelihood of a patient having a stroke based on age, BMI, and glucose level for a group of patients. To proceed with the implementation, different datasets were considered from Kaggle. Out of all the existing datasets, an appropriate dataset was collected for model building. After collecting the dataset, the next step lies in preparing the dataset to make the data clearer and easily understood by the machine. This step is called Data pre-processing. This step includes handling missing values, handling imbalanced data and performing label encoding that is specific to this particular dataset. Now that the data is pre-processed, it is ready for model building. For model building, pre-processed datasets along with machine learning algorithms are required. Logistic Regression, Decision Tree Classification algorithm, Random Forest Classification algorithm, K-Nearest Neighbour algorithm, Support Vector Classification, KMeans Clustering Classification and Naïve Bayes Classification algorithm are used. After building seven different models, they are compared using four accuracy metrics namely Accuracy Score, Precision Score, Recall Score, and F1 Score.

Template repo for Data Science for Biomedical Informatics (BMIN503/EPID600) final project

This diabetes prediction webapp. In this project, a Kaggle database is used to identify whether someone has diabetes based on data such as BMI, glucose level, blood pressure, etc

This is a basic bmi calculator written in python , it could have additional features latter and could become a fully developed health application or software

Hello friends this BMI-calculator are made with dart and flutter also I hope you will enjoy this project.

This is an End-to-End Data Science project which can predict whether a person has diabetes, or not, based on information about the patient such as blood pressure, body mass index (BMI), age, etc.