From Tabular Data to Images for AI Detection of in-Hospital Mortality for Patients with Myocardial Infarction

Artificial intelligence algorithms are widely used for analysis of data in all areas of science. Very often the data is collected and organized in a tabular form, representing a heterogeneous compilation of information with weak correlation, where traditional methods of investigation do not return good results. Transforming the representation of data from tabular form into images allows for more complex algorithms to be used in the analysis of the data. The current work examines the effect of data representation on the performance of a model built to predict mortality of patients diagnosed with myocardial infarction.