STM Journals Peer-reviewed research from Consortium e-Learning Network

Research and Reviews: A Journal of Health Professions Review Article

Natural Language Processing in Everyday Applications: From Classrooms to Clinics

  1. Aritro Chakraborty Department of computer Applications Echelon Institute of Technology Faridabad
  2. Sheetal Singh Department of computer Applications Echelon Institute of Technology Faridabad
  3. Khushi Singh Department of computer Applications Echelon Institute of Technology Faridabad
  4. Sujeet Kumar Department of computer Applications Echelon Institute of Technology Faridabad
  5. Mukesh Kumar Department of computer Applications Echelon Institute of Technology Faridabad

Abstract

Natural Language Processing (NLP) is transforming everyday sectors like healthcare and education by creating new opportunities for efficiency, accessibility, and early intervention. This paper investigates the function of natural language processing (NLP) in computer education. Tools like automated grading systems, intelligent tutoring assistants, and multilingual translation platforms are revolutionizing traditional teaching methods. Despite its benefits, adoption is still being slowed down by problems like data privacy, integration with education, and technical limitations. Simultaneously, natural language processing (NLP) is emerging as a useful healthcare ally that enables the early detection of cognitive decline through the detection of subtle alterations in speech patterns. In addition to techniques like lexico-syntactic and auditory analysis, models like BERT transformers and advanced machine learning classifiers are increasing the potential for non-invasive diagnosis. Early research in the field suggests a promising future despite challenges like limited data availability and low explainability. This study examines recent developments, highlights significant challenges, and forecasts the future of NLP in the domains of healthcare and education.

Keywords

References (11)

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