Natural Language Processing for Healthcare: Transforming Patient Data Analysis

Authors

  • Charlie White PhD
  • Rowan Phillips Dr.
  • Avery Gonzalez Prof.

Keywords:

Natural Language Processing, Healthcare, Machine Learning, Patient Data, Electronic Health Records

Abstract

This study investigates the role of natural language processing (NLP) in transforming the analysis of patient data within the healthcare sector. By leveraging machine learning algorithms, NLP can enhance the extraction and interpretation of unstructured data from electronic health records, improving patient outcomes. The article discusses the integration of NLP tools in healthcare systems and highlights the potential benefits and challenges associated with their implementation.

Author Biographies

Charlie White, PhD

PhD
University of Oxford
Wellington Square, Oxford OX1 2JD, United Kingdom

Rowan Phillips, Dr.

Dr.
University of Melbourne
Parkville, Melbourne, VIC 3010, Australia

Avery Gonzalez, Prof.

Prof.
Indian Institute of Technology Delhi
Hauz Khas, New Delhi, Delhi 110016, India

References

Kumar, N., & Kataria, V. Enhanced Sentiment Classification using a Multi-layered Stacked Ensemble Architecture.

KUMAR, Nitin; KATARIA, Vipin. Enhanced Sentiment Classification using a Multi-layered Stacked Ensemble Architecture.

Рагимов, Э. Р. (2006). Об одном подходе оценки риска при проектировании защищенных корпоративных сетей. Информационные технологии моделирования и управления, (1), 94-98.

Published

2024-12-24

Issue

Section

Articles