This website provides a platform for users to predict their likelihood of developing diabetes based on various factors.

This project uses machine learning to predict diabetes and provides explanations through SHAP and PCA, displayed in an intuitive user interface.

Implementing, describing and testing a single layer perceptron for predicting diabetes

This repository contains code for building a K-Nearest Neighbors (KNN) model to predict diabetes based on patient data. Includes data cleaning, hyperparameter tuning, and evaluation metrics.

CNN system analyzes retinal images & provides instant diagnoses, improving accuracy & reliability. The platform features a user-friendly interface implemented with Flask, allowing easy accessibility for users to upload images & to receive results.

Nested cross-validation implementation for the binary classification of healthy vs. diabetic patients.

A machine learning web application built using Streamlit that predicts whether or not a patient has diabetes.

This web app uses a machine learning model to predict the risk of diabetes based on patient data.

A Python-based system to predict diabetes using Machine Learning with Support Vector Machine (SVM). Includes data preprocessing, model training, and evaluation to achieve high prediction accuracy.

Early_Stage_Diabetes_Detection using Machine Learning

An open-source software platform for managing diabetes using a closed-loop insulin delivery system. The platform uses machine learning algorithms and continuous glucose monitoring to automatically adjust insulin dosing, improving glycemic control and reducing the risk of hypoglycemia.

An automated insulin delivery app for iOS, built on LoopKit

Deployed medical apps on streamlit

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

Diabetes Prediction System trained on various models out of which best model is selected for the application.

This one is advance version of the earlier one i.e Multiple disease prediction as we can run it just by cloning vs GitHub desktop and run it in vscode

Using machine learning to predict diabetes

This a multiple disease prediction based on user input which can predict upto 40 disease and trained on 131 parameters

this is combination of 3 different disease prediction system check readme for details