Examining Natural Language Processing Techniques in the Education and Healthcare Fields

Abstract

Natural language processing is a branch of artificial intelligence currently being used to classify unstructured data. While natural language processing is found throughout several fields, these algorithms are currently being excelled in the education and healthcare fields. The healthcare industry has found various uses of natural language processing models. These algorithms are capable of analyzing large amounts of unstructured data from clinical notes, making it easier for healthcare professionals to identify at-risk patients and analyze consumer healthcare perception. In the education field, researchers are utilizing natural language processing models to enhance student academic success, reading comprehension, and to evaluate the fairness of student evaluations. Both fields have been able to find use of natural language model processing models. Some business leaders, however, are fearful of natural language processing. This review seeks to explore the various uses of natural language processing in the healthcare and education fields to determine the benefit and disadvantages these models have on both fields.