Agentic AI for Glaucoma Detection

First-ever autonomous AI agent that orchestrates multiple deep learning models, performs self-reasoning, and generates evidence-based clinical reports through intelligent decision-making.

Launch Platform
94%
Detection Accuracy
<30s
Full Analysis
5+
AI Models
24/7
Availability

Multi-LLM Orchestration

Gemini 2.0, GPT-4, Qwen 2.5 working in parallel

Self-Reasoning Agent

Autonomous planning, reasoning & synthesis

Clinical-Grade Reports

PDF, HL7 FHIR, JSON export formats

How It Works: AI Pipeline

Real-time multi-modal deep learning with autonomous agent orchestration

Multi-Modal AI Fusion Architecture

Parallel Deep Learning Pipeline with Ensemble Intelligence

ReAct Framework Reasoning + Acting
THOUGHT
Reasoning
ACTION
Execute tools
OBSERVE
Analyze output
REFLECT
Self-evaluate
DECIDE
Next step
Iterative Reasoning Loop
INPUT LAYER
Fundus Image
Dimensions: 512×512
Channels: RGB (3)
Format: PNG/JPEG
AI AGENT PLANNING & ORCHESTRATION
Agents analyze task and plan tool usage
🎯 Planning
Agent
Workflow Design
Gemini 2.0
🔧 Tool Selection
Agent
Smart Routing
GPT-4
🧠 Reasoning
Agent
Analysis
Qwen 2.5
⚡ Coordination
Agent
Task Dispatch
Gemini 2.0
✅ Quality
Agent
Monitoring
GPT-4
LangGraph ReAct Pattern Multi-LLM
↓ Agents dispatch tools ↓
CNN Tool
Conv2D
EfficientNet-B4
256
128
64
Segmentation
ReLU • BatchNorm
Output
Cup/Disc Masks
IoU: 0.94
SVM Tool
ML
Radial Basis Function
Classification
γ=0.001
Output
Risk Probability
AUC: 0.98
YOLO Tool
v8
Object Detection
Detection
mAP: 0.92
Output
ROI Coordinates
Conf: 0.96
Google Tool
API
Web Search
Research
Real-time
Output
Citations
Context
↓ Tools return results ↓
AI AGENT SYNTHESIS & DISCUSSION
Agents collaborate to analyze tool outputs
🔍 Evidence Analysis
Reasoning Agent
Analyzing tool outputs:
CNN: CDR 0.68
SVM: 82% risk
YOLO: Detected ROI
Google: 15 studies
Qwen 2.5 • Chain-of-Thought
⚡ Evidence Fusion
Synthesis Agent
Combining insights:
Multi-modal agreement
Clinical correlation
Evidence strength
Gemini 2.0 • Fusion
✅ Quality Check
Validation Agent
Verification:
Consistency
✓
Completeness
✓
Medical validity
✓
Citation accuracy
✓
GPT-4 • Validation
Multi-Agent Collaboration
LangGraph Inter-Agent Communication Consensus Protocol
↓ Generating final report ↓
CLINICAL REPORT
Comprehensive Analysis
CDR Ratio
ISNT Rule
Risk Score
Recommendations
PDF • HL7 FHIR • JSON
4
Tools
5
Agents
Parallel
Execution
<30s
Inference
94%
Accuracy
PyTorch 2.0 scikit-learn Ultralytics LangGraph CUDA 11.8

Clinical-Grade AI Technology

Built on peer-reviewed research and validated clinical protocols

Deep Learning Architecture

EfficientNet-B4 backbone with custom heads for optic disc/cup segmentation achieving 99.2% IoU accuracy.

PyTorch ResNet-50

AI Agent Framework

LangGraph-powered autonomous agent with planning, reasoning, and reflection capabilities for clinical decision support.

LangGraph Gemini

CDR & ISNT Analysis

Automated cup-to-disc ratio calculation and ISNT rule verification following established clinical protocols.

CDR ISNT

Interactive Diagnosis

Conversational AI interface for differential diagnosis, treatment recommendations, and clinical queries.

NLP RAG

HIPAA Compliant

Enterprise-grade security with JWT authentication, encrypted storage, and comprehensive audit trails.

PostgreSQL MinIO

Clinical Reports

Automated generation of structured clinical reports with evidence citations and treatment recommendations.

PDF HL7