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MediScan: AI-Powered Medicine Identification

Introduction

MediScan started with a simple question: Why is it so hard to know what a pill actually does?

We've all been there – staring at a strip of tablets, trying to remember if it's for a headache or a stomach ache. The text is tiny, the names are complex, and Googling it often leads to scary (and irrelevant) WebMD articles.

I wanted to build a solution that was instant, accurate, and easy to use.

What is MediScan?

MediScan is a revolutionary mobile application that uses advanced artificial intelligence to identify medications from photos. The app is specifically designed to address healthcare challenges in rural and underserved areas, where access to pharmacists and medical professionals may be limited.

The Problem We're Solving

In rural communities worldwide:

  • Limited access to healthcare professionals for medication identification
  • Difficulties managing multiple medications, especially for elderly patients
  • Challenges with medication adherence due to confusion about pills
  • Language barriers when reading medication information

Our Solution

MediScan provides a simple, accessible way to:

  • Instantly identify medications through photo recognition
  • Access important medication information in plain language
  • Manage medication schedules and history
  • Connect with AI-powered support for medication questions

Core Features

  • 🤖 AI-Powered Identification: Simply snap a photo of a medicine, and our advanced AI will identify it, providing crucial information instantly.
  • 🩺 Focus on Rural Healthcare: Specifically designed to support healthcare workers and individuals in areas with limited access to medical resources.
  • 🔍 Detailed Medication Information: Access comprehensive details about identified medications, including usage instructions, side effects, and precautions.
  • 📱 User-Friendly Interface: Clean, intuitive design makes navigating the app simple for all users.
  • 🌐 Offline Functionality: Basic features work without an internet connection.

Technical Stack

  • Frontend: React with Vite, Tailwind CSS
  • Backend: Supabase (BaaS)
  • AI Models: Google Gemini Vision & Text APIs
  • Deployment: Vercel