🏥 Hospital Bed Management Dashboard

Made with ❤️ by Nipun Singh

See here - https://hospital-bed-management-dashboard.streamlit.app/

This project is an end-to-end Machine Learning-powered Hospital Bed Management System that predicts patient stay durations, dynamically allocates hospital beds, and visualizes critical statistics via an interactive Streamlit dashboard.

🚀 Features

• 📊 ML Prediction of patient stay using real hospital data.
• 🛏️ Dynamic Bed Allocation based on real-time admissions.
• ✅ Patient Admission & Discharge System
• 📈 Visual Analytics: ICU/Isolation/Ventilator needs, utilization rate, department distribution, and more.
• 🔍 Filter & Track patients based on diagnosis, department, and resource needs.
• 🧠 Trained ML Model (Linear Regression) included.
• 🗃️ SQLite Database Integration for persistence.
• 📦 Deploy-ready using Streamlit Cloud or any other platform.

📂 Files

• dashboard.py – Main Streamlit app
• model.pkl – Trained ML model for stay prediction
• hospital.db – SQLite database for patient & bed data
• hospital_data.csv – Sample data used for model training and simulation
• requirements.txt – Python package dependencies

🛠️ Tech Stack

• Python, Streamlit
• SQLite
• Pandas, NumPy, Scikit-learn
• Matplotlib (for graphs)

🧠 Machine Learning

• Model: Linear Regression
• Trained on real/simulated hospital data
• Predicts: length_of_stay_days based on:
  • Age
  • Acuity Score
  • Diagnosis
  • Department
  • Resource needs (ICU, Ventilator, Isolation)

🌐 Deployment

Easily deploy to Streamlit Cloud or run locally:

streamlit run dashboard.py