Medical Triage Analysis Workflow

📝

Stage 1: Patient Data Collection

📊 Input Data

Age: Patient age in years

Gender: Patient gender identity

Symptoms: Detailed symptom description

Duration: How long symptoms persist

History: Previous conversation context

⚡ Processing Method

Flask web framework receives POST request with JSON payload containing patient information.

Flask

JSON API

HTTP POST

✅

Stage 2: Data Validation & Sanitization

🔍 Validation Rules

All required fields present

Age is valid number

Gender field not empty

Symptoms description provided

Duration specified

🛡️ Security & Validation

Server-side validation ensures all required fields are present and properly formatted before processing.

4

Required Fields

100%

Validation Rate

🔧

Stage 3: AI Prompt Engineering

📝 Prompt Structure

System role definition

Patient demographics integration

Symptom context formatting

Structured output requirements

Medical guidelines reference

🎯 Prompt Optimization

Advanced prompt engineering creates comprehensive medical analysis instructions with specific output formatting requirements.

Prompt Engineering

Template System

Context Injection

🧠

Stage 4: AI-Powered Medical Analysis

🤖 AI Model Configuration

Model: Meta-Llama-3.1-70B-Instruct
Provider: Nebius AI Studio
Max Tokens: 2000
Temperature: 0.2 (Low randomness)
Top-p: 0.9 (High quality)

⚡ Processing Power

Large Language Model analyzes symptoms using medical knowledge to generate comprehensive triage assessment.

70B

Parameters

0.2

Temperature

2000

Max Tokens

🔍

Stage 5: Response Parsing & Extraction

📋 Extracted Sections

Urgency Level

Action Plan

Possible Conditions

Clinical Significance

Expected Evaluation

Follow-up Questions

Warning Signs

🎯 Parsing Algorithm

Regex-based extraction identifies structured sections from AI response, with intelligent fallback parsing for unstructured content.

Regex Parsing

Pattern Matching

Fallback Logic

🎨

Stage 6: Professional Report Formatting

🎨 Design Elements

Responsive CSS grid layout

Color-coded urgency indicators

Professional typography

Interactive hover effects

Mobile-optimized design

📄 Report Generation

Dynamic HTML generation creates professional medical reports with embedded CSS styling and structured content presentation.

HTML5

CSS3

Responsive Design

Dynamic Content

📋

Stage 7: Multi-Format Output Delivery

📤 Output Formats

JSON API response

Formatted HTML report

Structured sections object

Local file storage

Timestamp metadata

🚀 Delivery Pipeline

Final output includes multiple formats: API response for web integration, HTML for viewing, and optional local file storage for record keeping.

3

Output Formats

7

Report Sections