Inspiration
As international students in the United States, we've faced the daunting challenge of navigating an unfamiliar and complex healthcare system. Far from home and family, we've experienced firsthand how expensive and difficult it can be to access proper healthcare. This struggle inspired us to create VitalPath - a platform designed to bridge the gap between individuals and healthcare resources, ensuring people can stay informed about their health and seek attention before situations become critical.
What it does
VitalPath is a user-friendly web platform that:
- Collects self-reported health data from users
- Uses AI to analyze symptoms and predict potential health conditions
- Provides recommendations for managing health concerns
- Connects users to remote healthcare resources when urgent attention is needed
How we built it
Our development process involved several key components:
- Data Source: We utilized datasets from the CDC (Center for Disease Control and Prevention) to train our machine learning model.
- Machine Learning: We developed a custom AI model capable of analyzing health data and predicting potential conditions.
- Frontend: We built a responsive and intuitive user interface using React.
- Backend: While we haven't fully implemented the API yet, we've laid the groundwork for integrating our ML model with the web application.
Challenges we faced
Throughout the development of VitalPath, we encountered several challenges:
-Data Complexity: Working with health-related data required careful handling and interpretation. -ML Integration: Figuring out how to effectively integrate a machine learning model into a web application proved to be a complex task. -Time Constraints: Our ambitious goals were hampered by the hackathon's time limits, preventing us from fully implementing the API as initially planned.
Accomplishments that we're proud of
Despite the challenges, we're proud of several achievements:
- Developing a functional website that lays the foundation for our vision
- Training a machine learning model using real-world CDC data
- Creating a user-friendly interface for inputting health data
- Learning and applying new skills in a high-pressure, time-constrained environment
What we learned
This project was a significant learning experience for our team:
- Training and working with machine learning models for health predictions
- Developing responsive web applications using React
- Understanding the complexities of healthcare data and its applications
- Collaborating effectively as a team under tight deadlines
- Project planning and management in a hackathon setting
What's next for VitalPath
We're excited about the future of VitalPath. Our next steps include:
- Completing the integration of our trained model with the web application
- Implementing and optimizing the API for efficient data processing
- Continually refining our machine learning model to improve prediction accuracy
- Expanding our platform with additional features like health education resources
- Exploring partnerships with healthcare organizations to enhance our service offerings
Our ultimate goal is to evolve VitalPath into a comprehensive platform for health monitoring and assistance, with a particular focus on serving underserved communities and individuals navigating unfamiliar healthcare systems.
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