Skip to content

angimocc/ML-Healthcare-Platform

Repository files navigation

ML Healthcare Platform

Overview

Machine learning enables the discovery of patterns from medical data sources, providing robust prediction capabilities. This unified platform serves as a Doctor's assistant for predicting medical results while helping Patients effectively communicate with Doctors and maintain accessible medical records.

Our system leverages computational power alongside the doctor's expertise. The machine handles complex tasks and presents outcomes for the doctor’s confirmation.

Goals

Patients can securely share medical reports with doctors and receive prompt predictions. Doctors will analyze these reports using state-of-the-art Machine Learning and Deep Learning models provided by the platform. The ML/AI algorithms adapt in real-time, employing Reinforcement Learning based on doctors' input. Additionally, patients can track and access their medical records anytime with ease.

Technological Specifications

  • Backend: Python for ML/AI training and endpoints
  • Frontend: NodeJS and AngularJS for the web application
  • Features: Disease prediction and continuous learning algorithms

Models Implemented:

  • Diabetes classification: Using KNN and SVM
  • Breast Cancer Prediction: Using Convolution Neural Network
  • Liver Disease: Using KMeans
  • Skin Cancer Detection: Using Convolution Neural Network
  • Heart Disease Detection: Using Logistic Regression

This platform ensures advanced healthcare solutions powered by cutting-edge technology.

About

An advanced ML application assisting doctors in disease prediction and enabling patients to manage and share health records seamlessly.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors