A life-saving android application that predicts upcoming drops in blood sugar for diabetics

In this project, we try to predict whether someone is diabetic or not by using data mining techniques and approaches more accurately by combining the results of various machine learning (ML) techniques particularly K-Nearest Neighbors (KNN).

This repository consists of files required to deploy a Web App created with Flask on Microsoft Azure.# diabetes_predictor The project 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 a Kaggle database.

Used R to create a series of models to predict whether or not an individual is likely to have diabetes given a set of predictors, using a Diabetes dataset (768 obs. of 9 variables). Cleansed the data, created several visuals, and then selected the best model.

This project is using machine learning to predict the likelihood of a person having diabetes. The dataset used in this project is the "diabetes.csv" file, which contains information on various health factors such as glucose levels, blood pressure, BMI, and age, among others. The goal is to use this data to train a machine learning model, specifical

Design and Implementation of a Diabetic Disease Identification Algorithm Based on Data Mining. This one is developed as part of a Master's thesis project at Northeastern University, China. This project is supervised by Professor Chen Dongming.

Config files for my GitHub profile.

Repository for the paper "Spiking Neural Networks for Low-Energy Glucose Monitoring"

[THESIS] Detection Diabetes Mellitus Nails using Yolov7 Models Performance

Basics of machine learning is END-TO-END Repository which includes very Basic Machine Learning Models and Notebook

End-to-End project on diabetes prediction using IDE-Jupyter notebook, Flask with deployment on Heroku platform.

'21 한국통신학회 동계종합학술발표회 투고 논문, "XGBoost기반 당뇨병 예측 알고리즘 연구:2016~2018을 이용하여" 연구 과정 전반의 Open Archive입니다.

This project aims to predict diabetes, based on the dataset, done as a part of the Machine Learning Nanodegree program at Udacity.

In this project we are building a system that can predict weather a person has diabetes or not with the help of Machine Learning.

Machine Learning model trained to predict the possiblity of diabetes with Flask as a backend framework.

BBM409 Machine Learning Laboratory - Assignment 2 : Building Decision Tree From Scratch Using ID3 Algorithm and Diabetes Dataset

Diabetes Prediction Web Application

Diabetes Prediction Model for predicting whether the person is suffering from Diabetes or not

Predicting whether a person is diabetic or not using medical and demographic data from patients.

This repository contains a comprehensive implementation of machine learning algorithms for diabetes prediction. Using a diverse set of eight models, this project aims to accurately predict the occurrence of diabetes in individuals based on various input features.