EPIDERMA Skin Cancer Detection Portal

We propose a novel method of primary skin cancer prevention that integrates the following features into a cloud based web framework which optimizes the process of cancer detection

Objectives

• Design an interactive patient and doctor portal
• Provide an e-report generation system using Deep Learning
• Assist the doctors in Skin Cancer diagnosis and imaging tasks
• Equip the portal with a backend doctor database and a location & filter specific doctor recommendation portal
• Add a symptom and disease tagging support system based on NLP

Features

• Skin Cancer Probability Prediction
• Skin Tumor Detection
• Skin Cancer Type Classification
• Malignant Probability Prediction
• Skin Tumor Size Prediction
• DermaDroid Chatbot
• Doctor Recommendation System
• Report Generation System
• Discussion Forum
• Remedy Suggestion

Installation

OS X & Linux:

 git clone https://github.com/prakharsingh1312/Skin-Cancer-Detection.git SCD
 cd SCD
 virtualenv venv
 source venv/bin/activate
 pip3 install -r requirements.txt
 python3 app.py

Windows (Not Recommended as Pytorch has problems in installing):

git clone https://github.com/prakharsingh1312/Skin-Cancer-Detection.git SCD
cd SCD
virtualenv venv
./venv/Scripts/activate
pip3 install -r requirements.txt
python3 app.py

Meta

Naman Tuli – Email: namantuli2000@gmail.com - GitHub

Prakhar Singh – Email: prakharsingh13@gmail.com - GitHub

Contributing

1. Fork it (https://github.com/prakharsingh1312/Skin-Cancer-Detection/fork)
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -am 'Add some fooBar')
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request