💡 Inspiration: CuraCompanion was born from witnessing the daily struggles of elderly individuals and Alzheimer’s patients to manage medication and health vitals independently. The caregiving burden often leads to family burnout, and I wanted to build a solution that doesn't just treat the patient, but supports the entire support system. My goal was to create a digital health guardian that makes health management accessible, intuitive, and human-centric.
🛠️ How I built it: The project leverages a modern stack to ensure reliability: . Frontend: Built with Streamlit for a responsive, elderly-friendly interface with high-contrast accessibility. . Backend: Developed in Python using Pandas for vitals tracking and data visualization . Backend: Developed in Python using Pandas for vitals tracking and data visualization.
⚠️ Challenges I faced: . Data Parsing: Extracting structured data from unstructured PDF lab reports required significant iteration in prompt-engineering to ensure high accuracy with Gemini. . Version Control: I encountered difficulties managing large dependency folders, which taught me the critical importance of properly configuring .gitignore to maintain a clean repository. . UX Design: Designing for an elderly demographic meant stripping away complexity. I had to ensure the UI remained linear, high-contrast, and easy to navigate to minimize cognitive load
🎓 What I learned: This project reinforced the idea that the most powerful AI isn't just the most complex—it’s the one that is most accessible. Technically, I sharpened my Python skills and mastered building robust pipelines with the Gemini API. Above all, I learned "empathy in design." I realized that when building for vulnerable populations, every pixel and every word matters. Debugging my own technical hurdles only strengthened my resilience as a developer, and I am proud to have built a tool that provides independence to those who need it most.
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