OptiClarity 👁️💡

AI-Powered Eye Health Intelligence & Vision Diagnostics

🚀 Overview

OptiClarity is an AI-powered eye health application that combines deep learning, RAG-enhanced expert guidance, and intelligent scheduling. It leverages four deep learning models, including an ensemble model, for precise eye scan analysis. A Langchain-based chatbot, using a RAG pipeline, provides expert guidance, while a backtracking algorithm ensures conflict-free appointment scheduling for ophthalmologists and optometrists.

🏆 Features

✅ Deep Learning for Eye Scan Analysis – OptiClarity leverages four deep learning models, including an ensemble model that combines the strengths of individual models to enhance diagnostic accuracy. The tool is capable of analyzing various eye scans, such as OCT, Fundus, Slit Lamp, and Corneal Topography, for comprehensive eye health assessments.
✅ Smart AI Chatbot – Langchain-based chatbot using an advanced RAG pipeline for real-time, expert-level guidance.
✅ Conflict-Free Appointment Scheduling – Intelligent scheduling using optimized backtracking to ensure seamless booking for ophthalmologists and optometrists.
✅ Sleek and Mobile-Responsive UI – A user-friendly interface that is optimized for both web and mobile, ensuring smooth and efficient patient interaction.

📌 Technology Stack

• Deep Learning: TensorFlow, Keras, PyTorch, CNN architectures
• Models: ResNet50, MobileNetV2, InceptionV3, EfficientNetB3, Mistral7B
• Medical Imaging Preprocessing: Scikit-learn, NumPy, Pandas, Matplotlib, OpenCV
• Backend: Flask, FastAPI, Python
• Frontend: React.js, Lucide, Tailwind CSS
• Cloud & Deployment: AWS S3, Docker

🔬 How It Works

1️⃣ Input(s): Upload Scan images in dropbox Or Enter query in Optibot.
2️⃣ Step 1: Deep Learning Model extract patterns from eye scans by learning hierarchical features through convolutional layers to identify and classify eye conditions with high accuracy.
3️⃣ Step 2: RAG LangChain Optibot retrieves relevant information from an expert knowledge base and generates context-aware responses by combining retrieval with a language model, enabling real-time, reliable guidance.

🎯 Impact & Industry Validation

OptiClarity accelerates and enhances eye care, enabling:
✅ Instant bridging of the gap between early symptoms and diagnosis, potentially saving vision.
✅ AI-driven, multi-scan analysis that supports ophthalmologists in making faster, more accurate clinical decisions.
✅ Seamless integration of AI into real-world workflows, improving both patient experience and clinical efficiency.

🛠️ Getting Started

🔹 Prerequisites

• Python 3.8+
• Node.js v23.4.0
• TensorFlow & PyTorch installed

🔹 Installation

1️⃣ Clone the Repository

git clone https://github.com/YourUsername/AIM-OptiClarity.git
cd AIM-OptiClarity

2️⃣ Set Up the Frontend

cd frontend
npm install
npm run dev

3️⃣ Set Up the Backend

cd backend
pip install -r requirements.txt
run all the .py files
huggingface-cli login
enter your own huggingface tokens when required