Renal-AI: A 3-Day Kidney-Friendly Prevention Journey

A healthy student’s journey using Renal-AI to build a personalized 3-day kidney-friendly plan covering diet, sleep, and activity.

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Inspiration

The idea came from observing how kidney patients struggle with managing their diet, hydration, and lifestyle choices. We wanted to bridge the gap between medical recommendations and practical, day-to-day guidance. By using AI, we realized we could create customized wellness plans tailored to each user’s health metrics.

What it does

Renal-AI is an AI-powered platform that creates personalized 3-day wellness journeys for kidney health. Users receive tailored dietary, hydration, and lifestyle recommendations based on their health metrics. The platform tracks progress in real-time, helping users make informed decisions to improve kidney function and overall well-being.

How we built it

Data Collection: Gathered anonymized kidney health and dietary datasets.

AI Model Development: Built with Python and TensorFlow to generate personalized wellness plans.

Frontend: Designed with React, HTML, CSS, and JavaScript for a simple, intuitive interface.

Backend: Used Node.js and MongoDB for secure data storage and real-time tracking.

Integration: Combined AI insights with frontend recommendations to produce actionable 3-day plans.

Challenges we ran into

Limited Data: Finding high-quality, relevant kidney health datasets was difficult.

Balancing AI Accuracy with Simplicity: Ensuring recommendations were precise yet easy to follow.

Real-Time Personalization: Implementing adaptive plans that respond to daily user feedback.

UI/UX Design: Making the interface engaging without overwhelming users.

Accomplishments that we're proud of

Successfully built an AI-driven, user-friendly platform for kidney wellness.

Created personalized 3-day plans that make medical guidance actionable.

Developed a solution that demonstrates real-world impact in healthcare using AI

What we learned

Practical integration of AI/ML models into health applications.

Importance of user-centered design for non-technical users.

Challenges of handling health data privacy and validation.

Translating complex medical advice into simple, actionable guidance.

What's next for Renal-AI: A 3-Day Kidney-Friendly Prevention Journey

Expand Dataset: Include more diverse kidney health metrics to improve AI recommendations.

Enhanced Personalization: Make the platform adaptive to long-term user trends.

Mobile Application: Build a mobile-friendly version for on-the-go guidance.

Collaborations: Partner with healthcare providers to validate and extend the platform’s impact.

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