https://github.com/yuji1702/ai--powered-triage-system

This project implements a machine learning-based triage system for emergency rooms, which classifies patients based on their symptoms and vitals using a Random Forest Classifier. The system features real-time patient data integration, a user-friendly GUI built with Tkinter, and secure patient data encryption using Fernet from the cryptography lib
https://github.com/yuji1702/ai--powered-triage-system

cryptography data-imputation data-preprocessing data-security encryption gui healthcare machine-learning matplotlib medical-data python random-forest realt-time scikit-learn seaborn tkinter triage-system

Last synced: 4 days ago
JSON representation

This project implements a machine learning-based triage system for emergency rooms, which classifies patients based on their symptoms and vitals using a Random Forest Classifier. The system features real-time patient data integration, a user-friendly GUI built with Tkinter, and secure patient data encryption using Fernet from the cryptography lib

• Host: GitHub
• URL: https://github.com/yuji1702/ai--powered-triage-system
• Owner: Yuji1702
• Created: 2024-09-14T11:29:55.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-10-21T06:17:11.000Z (2 months ago)
• Last Synced: 2024-10-31T11:06:42.732Z (about 2 months ago)
• Topics: cryptography, data-imputation, data-preprocessing, data-security, encryption, gui, healthcare, machine-learning, matplotlib, medical-data, python, random-forest, realt-time, scikit-learn, seaborn, tkinter, triage-system
• Language: Python
• Homepage:
• Size: 6.84 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        


---

# AI-Powered Triage System for Emergency Rooms

This project implements an AI-powered triage system designed to streamline the triage process in emergency rooms by prioritizing patients based on the severity of their condition using machine learning techniques.

## Features

- *Patient Data Management*: Load, preprocess, and manage patient data from a CSV file.

- *Triage Classification*: The system determines a patient’s triage level based on their symptoms and vitals.

- *Machine Learning*: Utilizes a Random Forest Classifier to predict triage levels based on historical data.

- *Real-Time Data Integration*: Simulates real-time patient data and integrates it into the triage queue.

- *Graphical User Interface (GUI)*: Built with Tkinter to allow for easy data entry, display the patient queue, and visualize triage distribution.

- *Data Security*: Incorporates encryption and decryption of sensitive patient data using cryptography's Fernet module.

## Prerequisites

Install the necessary Python libraries using:

bash

pip install -r requirements.txt

requirements.txt includes:

- pandas

- numpy

- scikit-learn

- tkinter

- matplotlib

- seaborn

- cryptography

## Running the System

1. *Load Patient Data*: The patient data is loaded from a CSV file.

2. *Preprocess the Data*: The data undergoes preprocessing, which includes imputation of missing values, scaling of numeric data, and encoding of categorical variables.

3. *Model Training*: The system trains a Random Forest Classifier to predict triage levels.

4. *GUI*: The user can input new patient data via the GUI and view real-time updates of the triage queue and distribution graph.

To run the program:

bash

python main.py

## GUI Overview

The GUI enables the user to:

- Enter patient details like age, gender, symptoms, and vitals.

- View the patient queue sorted by triage level.

- See a graphical representation of the current triage level distribution.

## Encryption & Decryption

Patient data is encrypted using the Fernet encryption system to ensure confidentiality.

---

This structure includes essential project details, setup instructions, and how to run the system. Let me know if you need any specific tweaks!