AI HEALTH GUIDANCE

Inspiration

Inspiration

Access to quick, reliable health guidance isn't always easy — people often turn to search engines with vague symptoms and get overwhelming or unreliable information. We wanted to build something simple that gives people a starting point for understanding their symptoms, tracking basic health metrics, and knowing what to do in an emergency, all while being clear that it's a guide, not a replacement for real medical care.

What it does

AI Health Guardian is a wellness companion web app with:

• An AI-style Symptom Checker that matches user input against a database of 25+ common conditions and returns a suggestion with a confidence level (Low/Medium/High)
• A BMI Calculator that gives instant feedback and personalized health tips
• Daily Health Tips covering nutrition, hydration, exercise, sleep, and mental wellness
• An Emergency Assistance section with a one-tap Call 108 button and clear warning signs for when to seek immediate help
• A Nearby Hospitals finder that opens Google Maps
• A live Health Dashboard tracking BMI status, water intake, and an overall health score

How we built it

The site is built with plain HTML, CSS, and JavaScript, keeping it lightweight and easy to deploy. We used a symptom-matching database with multiple keyword groups per condition so the checker recognizes different ways people phrase the same symptom (e.g. "can't breathe," "shortness of breath," "breathless" all match the same result). The design follows a professional blue-white-green medical theme with smooth animations and card-based layouts for clarity on any device.

Challenges we ran into

Getting the symptom checker to feel intelligent without an actual AI backend was the biggest challenge — we solved this by building a much larger keyword database with multiple phrasing variants per symptom, rather than a simple rigid if/else structure. We also learned the importance of file path consistency (spaces in filenames breaking image loading) and worked through deploying the project live via GitHub Pages for the first time.

What we learned

We learned how to structure a multi-section responsive site from scratch, debug real deployment issues (broken image paths, Live Server setup, GitHub Pages configuration), and think carefully about how to communicate health information responsibly — including clear disclaimers that the tool is educational, not diagnostic.

What's next for AI Health Guardian

Future plans include connecting a real AI/NLP model for more accurate symptom interpretation, adding user accounts to track health history over time, and expanding the hospital finder with real-time location-based results.

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for AI HEALTH GUIDANCE

Built With

• css
• git
• github
• healthtech
• html
• javascript
• vscode
• webdevelopment