A Comparative Study of Natural Language Processing Algorithms for Electronic Medical Records

Abstract

Electronic Medical Records (EMR) contains large amount of information. It is very helpful for patient treatment if we extract all available information in systematic manner. There are various methods for annotation of medical records but all methods identify different annotation. Therefore, we have designed a visualized system to consolidate multiple annotators of different NLP algorithm. We have compared various annotation techniques and combination of various annotation techniques based on runtime and batch window processing.