As there is no consensus about how to store the results of echocardiography examinations, information extraction from them is a non-trivial task. Successful named entity recognition (NER) is key to getting access to the stored information and the process of identification has been recognized as a bottleneck in text mining. Our goal was to develop and compare such NER methods that are capable of achieving this task. Our practical results show that the text mining-based NER method is able to perform at a similar level in finding and identifying terms as the regular expression-based NER method. The paper highlights the advantages and disadvantages of both methods.