Optimizing Chemotherapy Schedules for Hodgkin's Lymphoma ⚕️

Project Overview

This project presents a web application designed to optimize chemotherapy schedules for Hodgkin's Lymphoma patients. The system leverages the Simulated Annealing algorithm to create personalized treatment plans that balance treatment efficacy with patient tolerance and recovery capabilities. The application dynamically adjusts schedules based on real-time patient health metrics and responses to minimize adverse side effects and enhance overall treatment success.

🚀 Features

• Personalized Scheduling: The application tailors treatment plans based on individual patient data, including disease stage, heart/lung health, and the presence of bulky tumors.
• Dynamic Adaptation: The schedule is dynamically adjusted after each treatment cycle based on patient-specific data, such as treatment tolerance, blood cell counts, and tumor response.
• Simulated Annealing Algorithm: This probabilistic optimization algorithm is used to explore a wide solution space and avoid local minima, ensuring the final schedule is both effective and adaptable.
• Web-based Interface: A simple web application built with Python's Flask framework allows for easy user input and visualization of the optimized schedules.

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🛠️ Technologies Used

• Design Technique: Simulated Annealing
• Backend Framework: Flask (Python)
• Algorithms: Simulated Annealing, math, random
• Frontend: HTML, CSS

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⚙️ Setup and Installation

Follow these steps to get the application up and running on your local machine.

Prerequisites

• Python 3.x
• pip (Python package installer)

1. Install Dependencies 📦

It is highly recommended to use a virtual environment to avoid conflicts.

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On macOS/Linux
source venv/bin/activate
# On Windows
.\venv\Scripts\activate

# Install the required Python packages
pip install Flask

2. Run the Application ▶️

Once you have the dependencies installed, you can launch the Flask application from the project's lymphoma_web directory.

python app.py

The application will start, and you can access it by opening your web browser and navigating to http://127.0.0.1:5000/.

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💬 Usage

• Initial Input: On the homepage, enter patient data including disease stage, heart and lung health percentages, and whether bulky tumors are present.
• View Results: The application will display an initial and an optimized chemotherapy schedule.
• Dynamic Adjustments: After each treatment cycle, input updated patient data to allow the algorithm to adjust the schedule for the next cycle.