One of the major challenges related to breast cancer is late detection. If detected early, many lives can be saved. Unfortunately, conventional diagnostic methods are often inaccessible, especially in remote or underprivileged areas.
This inspired us to build PinkAware — a comprehensive and inclusive platform that not only aids in early detection of breast cancer using ultrasound imaging and machine learning, but also provides end-to-end support throughout the patient's medical journey.
- Uses a trained ML model on ultrasound images to assess breast cancer risk.
- Provides a risk score with actionable guidance.
- Appointments: Book consultations with doctors.
- Lab Tests: Schedule and manage lab tests.
- Medications: Track and manage medication regimens.
- Community Chat: Discuss and share experiences.
- Nearby Zone: Connect with nearby community members during medical emergencies.
- Volunteer Zone: Participate in awareness/support events.
- Fundraiser Zone: Donate for patients unable to afford treatment.
- Trained on a breast cancer knowledge base to answer doubts and assist users in navigating the platform.
- ML Model: Built using Python and Flask.
- Frontend: Bootstrap, EJS, JavaScript, CSS.
- Backend: Node.js, Express, MongoDB, Mongoose.
- Auth: Google OAuth.
- Email Support: Nodemailer.
- Hosting: Render (Note: ML model and Nearby zone currently work only on localhost).
- Finding the right dataset.
- Building an intuitive, mission-aligned UI.
- Integrating Python-based ML into a JS stack.
- Deployment of local-only Python scripts.
- Beautiful and intuitive user interface.
- Effective ML model aiding early detection.
- Fully inclusive and community-driven healthcare platform.
- Real-world healthcare problem-solving.
- Creating engaging, user-first platforms.
- Breaking down large-scale projects into modular tasks.
- Online hosting of ML & Nearby zones.
- Language localization.
- Partnership with hospitals/NGOs.
- Enhanced chatbot with more medical data integration.
- Frontend: Bootstrap, EJS, JavaScript, jQuery
- Backend: Node.js, Express, MongoDB
- ML & Imaging: Python, Flask
- Utilities: Google OAuth, Nodemailer
🌐 Live Website: https://pinkaware.onrender.com
🔗 GitHub Repositories:
- Web & Platform: https://github.com/Vidit0018/PINK
- ML Model: https://github.com/mohitarora8181/ultrasound-detect
🧪 Demo Credentials (Localhost-Only for ML & Nearby Zone):
Username: eminem
Password: eminem