SYSTEMATIC REVIEW article
Front. Artif. Intell.
Sec. Natural Language Processing
This article is part of the Research TopicThe Use of Large Language Models to Automate, Enhance, and Streamline Text Analysis Processes. Large Language Models Used to Analyze and Check Requirement Compliance.View all 5 articles
Impact of Natural Language Processing Models on Diagnosis and Decision-Making in Healthcare, Business, Education, and Sports: A Review
Provisionally accepted
- Vellore Institute of Technology, Chennai, Chennai, India
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Natural Language Processing (NLP) has an influence on almost every field nowadays, such as business, healthcare, and sports, by making advanced interactions with human language and providing analytics. In the field of business, NLP has been a revolution, bettering customer service with the help of advanced chatbots, sentiment analysis, and automation in generating content, which enhances efficiency, personalization, and most importantly, decision-making. In healthcare, NLP is of crucial importance in decoding unstructured data like of medical records, supporting diagnostic accuracy, and making patient communication smoother, leading to better outcomes and improving efficiency. When it comes to sports, NLP provides critical insights through performance analytics, media content interpretation, and improved fan engagement, transforming data to utilize it for our advantage. The aim of this review is to systematically evaluate NLP's effectiveness across these sectors, address possible and existing challenges, and propose approaches for future research. Through the integration of case studies and performance assessments, we seek to clearly explain how NLP promotes innovation, resolves complex issues, and has made contributions to advancing new heights in these domains.
Keywords: Natural language processing(NLP), BERT, Customer RelationshipManagemen(CRM), Named Entity Recognition(NER), Business Process Modeling(BPM), Artificial intelligence(AI), Electronic Health Records (EHR), ConvolutionalNeural Networks(CNN)
Received: 16 Sep 2025; Accepted: 10 Dec 2025.
Copyright: © 2025 Choudhary, Pamidimokkala, R and M. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Krithiga R
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