Backend (Flask) and Frontend (HTML, CSS, and JavaScript) for an AI-based Medical project.
Jupyter NotebookGPL-3.0
HealthCure: An All-in-One Medical Solution
This project will detect seven major diseases under one platform which are as follows:
Covid 19 Detection
Brain tumor detection
Breast Cancer detection
Alzheimer detection
Diabetes detection
Pneumonia detection
Heart disease detection
It is a revolutionary project as it can detect the disease with a few clicks at home with a good
accuracy and no need to wait for days for the reports. Accordingly, the disease can be treated
quickly. AI is a booming technology and it can do wonders that humans cannot even imagine. This
project will detect seven diseases using CNN (Convolutional Neural Networks) which will
take input images, assign importance (learnable weights and biases) to various aspects/objects in
the image, and be able to differentiate one from the other. With time, more datasets will be available which will improve the accuracy of this project. This project can be expanded to any number of diseases in the future as well.
Tools and Technologies
Python - Jupyter Notebook (TensorFlow for Model Training)
Flask Web Framework (for Backend)
Google Firebase (for Real-Time Storage and Firestore Database)
HTML, CSS, and JS (for Frontend)
Runtime
Python v3.8.10
Dataset
The dataset for the project was gathered from multiple sources. Two of them are as follows: