Big Data In Healthcare: Paris Hospitals Predict Admission Rates Using Machine Learning

Hospitals in Paris are trialling Big Data and machine learning systems designed to forecast admission rates – leading to more efficient deployment of resources and better patient outcomes. The result was the first contribution to an open source framework of code designed to carry out the analysis over a scalable, distributed framework. Machine learning is employed to determine which algorithms provide the best indicator of future trends, when they are fed data from the past. The core of the analytics work involves using time series analysis techniques – looking for ways in which patterns in the data can be used to predict the admission rates at different times. This code is already being put to use in several other projects involving healthcare and finance.