A review on applied Natural Language Processing to Electronic Health Records

Over the last decades, the healthcare sector has witnessed massive growth in the use of various information technologies such as Electronic Health Records (EHRs), a digital version of a patient's paper chart that electronically stores all information related to patient care. After the emergence of the EHRs, a large amount of language data is being produced. This data is a collection of documents or text files that include essential information, but most of them are unstructured to be properly analyzed by computers. To handle the human language complexity and make this data more machine-analyzable, researchers often rely on using Natural Language Processing (NLP) techniques. This paper presents a review that features the application of NLP and machine learning to EHRs and present associated challenges. Besides, we outline various applications and initiatives in the healthcare sector. Finally, we provide promising directions for future research.