Functional prototype for estimating surgery rooms’ usage time with data mining techniques

Abstract

The goal of this project is to create a stand-alone prototype for optimizing operating room administration utilizing data mining techniques. The project will collect historical data on operating room utilization and train a machine-learning model that can forecast the time required for each type of surgical operation using a data-driven approach. The model proposed originates from the analysis of different data management algorithms in order to obtain different approaches to the same problem and to validate the accuracy and reliability of these algorithms in the surgery time optimization.