🏥 TriageOS: Advanced Patient Flow & Critical Care System

TriageOS is a hybrid medical software solution designed to solve the "ER Bottleneck" problem. It combines a high-performance C++ backend (optimized for mathematical sorting efficiency) with a modern Python dashboard (for real-time visualization).

Unlike standard hospital systems that use basic First-In-First-Out (FIFO) or simple Priority Queues, TriageOS utilizes a Fibonacci Heap data structure to achieve $O(1)$ constant-time complexity for critical operations, ensuring that patient care is never delayed by software lag during mass casualty surges.

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🚀 Key Functionalities

🩺 Medical Features

• Smart Triage Queue: Automatically prioritizes patients based on the Emergency Severity Index (ESI) (1=Critical to 10=Non-Urgent).
• Dynamic Deterioration Engine: Allows instant re-triage. If a patient in the waiting room (Priority 4) suffers a cardiac arrest, their priority can be updated to Priority 1 instantly.
• Mass Casualty "Merge" Protocol: In the event of a disaster (e.g., bus crash), the system can merge a secondary list of incoming ambulance patients into the main hospital queue in $O(1)$ time.
• Live Vitals Monitor: Visualizes real-time patient status including Heart Rate (BPM), Blood Pressure, and SpO2 with an animated EKG graph.
• LWBS (Left Without Being Seen): Efficiently handles patients who walk out, removing them from the queue to maintain accurate wait-time statistics.

⚙️ Technical Engineering

• Hybrid Architecture: Uses a custom subprocess bridge to allow Python to visualize low-level C++ memory operations in real-time.
• "No-STL" Compliance: Built strictly using Raw C++ Arrays and manual memory management.
  • No std::vector: Replaced with a custom NodeVector struct with dynamic resizing logic.
  • No std::unordered_map: Replaced with a Direct Address Table (nodeLookup[10001]) for instant $O(1)$ access without hash collisions.
• Secure Authentication: Implements a salted DJB2 Hashing Algorithm to secure user credentials (passwords are never stored in plain text).

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📐 Algorithmic Efficiency

Why use a Fibonacci Heap? In a high-volume ER, seconds matter. Standard Binary Heaps slow down as the queue grows.

Operation	Standard System (Binary Heap)	TriageOS (Fibonacci Heap)	Real-World Scenario
Insert Patient	$O(\log n)$	$O(1)$ (Instant)	50 patients arrive at once during a surge.
Update Priority	$O(\log n)$	$O(1)$ (Instant)	A patient's appendix bursts while waiting.
Merge Queues	$O(n)$	$O(1)$ (Instant)	Integrating an ambulance convoy list.
Discharge (Extract)	$O(\log n)$	$O(\log n)$	Doctor treats the next most critical patient.

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📂 Project Structure

TriageOS/
├── src/                    # THE C++ ENGINE
│   ├── Auth.cpp            # Security & Hashing Logic
│   ├── Auth.h              # Header for Auth
│   ├── FibHeap.cpp         # The Core Fibonacci Heap Algorithms
│   ├── FibHeap.h           # Header for Heap
│   ├── Node.cpp            # Patient Logic (Circular Linked Lists)
│   ├── Node.h              # Header for Node
│   ├── System.cpp          # Command Processor & Bridge Logic
│   └── System.h            # Header for System
│
├── medical_gui.py          # THE PYTHON DASHBOARD (Frontend)
├── users_db.txt            # Encrypted User Database
├── patients_data.txt       # Patient Persistence File
└── README.md               # Documentation