Application of Named Entity Recognition Methods to Extract Information from Echocardiography Reports

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.