A synthetic dataset of liver disorder patients

The data in this article include 10,0 0 0 synthetic patients with liver disorders, characterized by 70 different variables, in-cluding clinical features, and patient outcomes, such as hos-pital admission or surgery. Patient data are generated, sim-ulating as close as possible real patient data, using a pub-licly available Bayesian network describing a casual model for liver disorders. By varying the network parameters, we also generated an additional set of 500 patients with character-istics that deviated from the initial patient population. We provide an overview of the synthetic data generation process and the associated scripts for generating the cohorts. This dataset can be useful for the machine learning models train-ing and validation, especially under the effect of dataset shift between training and testing sets.(c) 2023 Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )