Report: Challenges in Natural Language Processing Use Cases

This report delves into the challenges associated with the use cases of Natural Language Processing (NLP). It begins by defining NLP as a field of Artificial Intelligence that allows machines to understand and generate human language. The report then discusses several use cases of NLP, including disease prediction using electronic health records, analyzing customer feedback from social media, and developing cognitive assistants. However, the report identifies various challenges, such as the potential for inaccurate results in disease diagnosis due to the low accuracy of NLP features. It concludes that, despite the increasing advancement, complexities still exist in the performance of NLP, which are regularly experimented by several companies.

Running head: CHALLENGES FOR THE USE CASE OF NLP
Challenges for the use case of NLP
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1CHALLENGES FOR THE USE CASE OF NLP
Table of Contents
Introduction:....................................................................................................................................3
Discussion:.......................................................................................................................................3
Challenges for the use case of NLP:............................................................................................3
Conclusion:......................................................................................................................................4
References:......................................................................................................................................5

2CHALLENGES FOR THE USE CASE OF NLP
Introduction:
Natural Language Processing or NLP is defined as the field concerned o Artificial
Intelligence that allows machines to read, understand and generate meanings from the human
languages. The discipline of NLP is focused on interacting human languages with the help of
data science technology and is applicable to a variety of industries. This part of the report is
prepared so as to reflect on the challenges faced by many of the use case of the application of
NLP while determining the presence of any downsides within those applications.
Discussion:
Challenges for the use case of NLP:
There are variety of use cases that are associated with NLP which includes
 Recognition or prediction of diseases with the help of electronic health record and
patient’s own speech,
 Helping organizations to determine the customers about the services while identifying
and generating information from social media sources (Yse, 2015).
 In developing cognitive assistant to provide personalized search that includes learning
and reminding of names or any information during times of need.
With the application of NLP in all these use cases certain challenges do exist within one of its
application while analyzing queries of large samples of search engines where it is being
identified (Yse, 2015) by many of the internet users were found to suffer from pancreatic cancer
even before the diagnosis result of the disease was received. This leads to evolvement of

3CHALLENGES FOR THE USE CASE OF NLP
challenges where the diagnosis result may happen to be tested falsely due to low accuracy
feature of the NLP leading to inability to meet the projected rates.
Conclusion:
Hence from the report it can be concluded that in spite of various use cases of the
application of NLP, certain complexities do exist with the performance of Natural Language
Processing that are regularly experimented by several companies leading to initiate interactions
between computers and human through natural languages. Although the future of NLP looks
quite challenging but its level of advancement is increasing gradually day by day.

4CHALLENGES FOR THE USE CASE OF NLP
References:
Diego Lopez yse. D. (2015). Your Guide to Natural Language Processing (NLP). Retrieved
from https://towardsdatascience.com/your-guide-to-natural-language-processing-nlp-
48ea2511f6e1