FEM-CARE is an artificial intelligence–powered women’s health assistance platform designed to help users understand and manage symptoms related to PCOS (Polycystic Ovary Syndrome) and hormonal health challenges. The platform combines machine learning, symptom tracking, data visualization, and an empathetic wellness chatbot to provide personalized insights and emotional support in a single, unified application.
FEM-CARE AI focuses on accessibility, privacy, and user comfort, offering actionable wellness guidance rather than clinical diagnosis.
PCOS affects a significant portion of the global female population, yet early awareness, consistent symptom tracking, and emotional support remain limited. Many users struggle to interpret symptoms or track long-term changes in their health.
FEM-CARE aims to bridge this gap by providing intelligent symptom analysis, progress tracking, and mental wellness support in a safe and easy-to-use digital platform.
- User login and signup with protected data handling
- Privacy-first approach for sensitive health information
- Simple and guided form for PCOS-related symptom logging
- Input validation for accurate and consistent data collection
- Machine learning–based PCOS severity prediction
- Uses models such as Random Forest for fast and reliable results
- Provides interpretable outputs with confidence awareness
- Tracks symptom history over time
- Visualizes health progress using graphs and analytics
- Identifies improvement, stability, or worsening patterns
- Lifestyle guidance tailored to user data
- Includes diet, exercise, and sleep suggestions
- NLP-based conversational assistant
- Provides emotional support, stress-relief techniques, and motivation
- Designed to promote mental well-being alongside physical health
- Clean, calming, and accessibility-friendly interface
- Intuitive navigation and consistent visual design
- Custom branding and logo
- User signs up and logs in securely
- Symptoms are recorded through a guided input interface
- Machine learning model predicts PCOS severity
- Results and wellness tips are displayed to the user
- Symptom trends are tracked and visualized over time
- Chatbot offers ongoing emotional and mental wellness support
Frontend:
- Next.js
- Tailwind CSS or Chakra UI
- Charting libraries such as Chart.js or Recharts
Backend:
- Node.js with Express
- RESTful APIs
- Secure authentication and session handling
Machine Learning:
- Python
- Scikit-learn
- Random Forest or similar classification models
Database:
- MongoDB
- Secure storage for user profiles and symptom history
- User data is stored securely and never shared publicly
- Strong emphasis on confidentiality and consent
- The platform provides decision support, not medical diagnosis
- Transparent communication of AI limitations
- Wearable device integration
- Advanced personalized recommendations
- Multilingual chatbot support
- Doctor or expert dashboard (opt-in)
- Mobile application version
Contributions are welcome in frontend development, backend APIs, machine learning, testing, and documentation.
FEM-CARE AI is intended for educational and wellness support purposes only. It does not replace professional medical advice, diagnosis, or treatment. Users should consult qualified healthcare professionals for medical concerns.