Project Overview

• This project aims to address the memory-related challenges faced by elderly individuals, specifically those aged 50 to 90, who struggle with recalling old memories and experience memory loss due to lifestyle factors that can lead to mild cognitive impairment (MCI) or Alzheimer's disease. To mitigate these difficulties and improve their quality of life, we have developed a Deep Learning Model, Website, and Mobile application.

• The mobile application serves as a comprehensive memory assistance tool for MCI or Alzheimer's patients, providing them and their families with valuable resources and support. Users can access important information, manage daily activities, and track medication adherence through the application. Additionally, the app facilitates communication between patients and dedicated volunteers, enhancing language recall and social interaction through video chat functionality.

• The website enhances the project by providing a platform that facilitates the mission of doctors in assisting patients. Doctors can access the website to review patient data, conduct video conferences with patients and their families, and make informed decisions regarding their care.

• The website also integrates an advanced artificial intelligence (AI) model capable of detecting various types of Alzheimer's disease and mild cognitive impairment. This model analyzes patient MRI scans to predict the presence and progression of these conditions, further assisting doctors in providing accurate diagnoses and personalized treatment plans.

ADNI Dataset

Alzheimer’s Disease Neuroimaging Initiative (ADNI) collected from the website based on MCI Paper

Data Analysis

Meta Analysis

MRI Analysis

System Architecture (How it Works)

We have created this "How it Works" when participating in Microsoft Imagine Cup

Project Management (GitHub & Drive & Discord)

We used GitHub Project Board to manage our tasks using the GitHub Flow

We keep tasks organized using issues

We have used Discord Server to organize discussions for everything (Chat between team made easy)

Implementation

Mobile App

Model Implementation

Website (Backend & Frontend)

Technologies

We have used many technologies as we have website, mobile, ML and we do all of that on GitHub and Azure

Competitions

Participated in Four Competitions

Winner of MLH Hackathon (Hack & Wellness 2). Link to Hackathon

Participated in Three Hackahtons on MLH

Our Team

• Omar Elsherif - Machine Learning & Data Analysis - LinkedIn
• Ahmed Tarek - Machine Learning & Data Analysis - LinkedIn
• Anas Osama - Backend Django - LinkedIn
• Amr Atif - Backend Django - LinkedIn
• Mohamed Tabana - Mobile and DevOps - LinkedIn
• Esmael Mosaad - Frontend React - LinkedIn