Examining Natural Language Processing Techniques in the Education and Healthcare Fields
Vijaya Kanaparthi

Vijaya Kanaparthi, Leading Technology Organization, USA.

Manuscript received on 05 October 2022 | Revised Manuscript received on 19 October 2022 | Manuscript Accepted on 15 December 2022 | Manuscript published on 30 December 2022 | PP: 8-18 | Volume-12 Issue-2, December 2022 | Retrieval Number: 100.1/ijeat.B38611212222 | DOI: 10.35940/ijeat.B3861.1212222
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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. 
Keywords: Artificial intelligence- the development and theory of computer systems completing complex, human tasks (Lucini et. al., 2021 [3]).
Scope of the Article: Artificial Intelligence