ClinIQ — Clinical Decision Support System

A rule-based Clinical Decision Support System that analyzes patient data and returns structured clinical alerts with predictive risk scoring.

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Stack

Frontend — React 19, Vite 7, Tailwind CSS v4, Framer Motion
Backend — FastAPI, Python 3.10+, Uvicorn

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Quick Start

Backend

cd backend
pip install -r requirements.txt
uvicorn main:app --reload

Runs at http://localhost:8000 — API docs at http://localhost:8000/docs

Frontend

cd frontend
npm install
npm run dev

Runs at http://localhost:5173

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API

GET / — Health check

POST /analyze_patient — Analyze patient data

// Request
{
  "age": 65,
  "allergies": ["penicillin"],
  "medications": ["amoxicillin", "aspirin", "warfarin", "metformin"],
  "glucose": 240,
  "systolic_bp": 150,
  "diastolic_bp": 95,
  "heart_rate": 125
}

// Response
{
  "alerts": [...],
  "total_alerts": 6,
  "risk_score": 9,
  "risk_level": "HIGH",
  "status": "critical"
}

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Clinical Rules — 21 Active

Category	Rules
Vital Signs	Tachycardia, Bradycardia, Stage 1 & 2 Hypertension, Hypotension, Elevated BP, Elevated Pulse Pressure, Shock Pattern
Metabolic	Severe Hyperglycemia, Hyperglycemia, Hypoglycemia, Pre-Diabetes, Metabolic Syndrome
Medication Safety	Allergy Conflicts, 6 Drug Interactions, Polypharmacy, Elderly Polypharmacy (Beers), Renal Risk (Metformin)
Risk Indicators	Age-based Cardiovascular Risk, High-Risk Medication Monitoring

Risk Scoring

Score	Level
0 – 2	LOW
3 – 5	MODERATE
6+	HIGH

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Features

• Clean light-theme dashboard with two-column layout
• 7-field patient assessment form with inline clinical hints
• Expandable alert cards — detected value, normal range, recommended action
• Animated risk score card with progress indicator
• One-click demo patient for instant testing

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Demo Patient

Click Load Demo in the form to auto-fill a high-risk profile:

Field	Value
Age	65 yrs
Allergies	penicillin
Medications	amoxicillin, aspirin, warfarin, metformin
Blood Glucose	240 mg/dL
Blood Pressure	150 / 95 mmHg
Heart Rate	125 bpm

Expected: 6+ alerts · HIGH risk

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Codezen Round 2 — Clinical AI Track