Team
Shrey Patel, Suyash Kulkarni, Kaverappa K U, Yash Modi
Categories
Artificial Intelligence, Data Analysis, Deep Learning, Machine Learning, Python
Overview
This project aims to predict healthcare wait times using both classical machine learning algorithms and deep learning methods, specifically LSTM networks. It focuses on forecasting three types of wait durations: referral, decision, and admit times. The dataset includes patient demographics and referral-related information, which underwent thorough preprocessing and feature engineering to enhance model performance. Classical models like Random Forest and Gradient Boosting were implemented alongside LSTM models to explore both structured and sequential approaches. The goal is to support healthcare systems in improving planning, resource allocation, and patient flow management by providing accurate and timely wait time predictions.
Predicting Patient Wait Times - Waypoint healthcare
