This article explores some new and emerging applications of text analytics and NLP in healthcare. Each application demonstrates how HCPs and others use natural language processing to mine unstructured text-based healthcare data and then do something with the results. Healthcare databases are growing exponentially, and text analytics and natural language processing (NLP) systems turn this data into value. Healthcare providers, pharmaceutical companies and biotechnology firms all use text analytics and NLP to improve patient outcomes, streamline operations, and manage regulatory compliance. In fact, 26 million people have already added their genetic information to commercial databases through take-home kits.

There has been a significant growth in the volume and variety of data because of the accumulation of unstructured text data. Companies are now relying on technologies like text analytics and Natural Language Processing (NLP) for making sense of such massively collected data. Text analytics and NLP hold the key to unlocking the business value within these huge data sets. NLP is concerned with making natural language accessible to machines, while text analytics refers to the extraction of useful information from text sources. Today, text analytics and NLP are gradually transforming into a field extremely useful for various business applications, such as competitive analysis, and improving the quality of machine intelligence systems.