Predictive Hospital Resource Allocation Model

Design a machine learning pipeline using Python that predicts hospital resource requirements with 90% accuracy. Develop a comprehensive model that analyzes historical patient admission data, seasonal trends, and community health indicators to forecast bed occupancy, staff scheduling, and medical supply needs. Utilize advanced feature engineering techniques with pandas, implement gradient boosting models, and create an interactive dashboard using Dash or Streamlit that allows hospital administrators to simulate different scenarios.