Examining NLP for Smarter, Data-Driven Healthcare Solutions

Examining NLP for Smarter, Data-Driven Healthcare Solutions

Nitesh Upadhyaya (Globallogic Inc., USA), Herat Joshi (Great River Health System, USA), and Chetan Agrawal (Radharaman Institute of Technology and Science, India)
Copyright: © 2025 |Pages: 28
DOI: 10.4018/979-8-3693-8990-4.ch017
OnDemand:
(Individual Chapters)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

This chapter delves into the critical role of Natural Language Processing (NLP) in the healthcare sector, with a focus on its current applications and future potential. It examines how NLP enhances clinical documentation, decision support systems, and patient-provider communication. The chapter also examines problems such as data privacy, security, bias, and model interpretability, which prevent NLP from being fully integrated into healthcare systems. Solutions such as explainable AI, regulatory compliance, and interdisciplinary collaboration are proposed to overcome these barriers. The chapter further explores advancements in deep learning models, cross-language NLP, and predictive analytics that are poised to revolutionize healthcare by providing more personalized, data-driven care. Overall, the chapter emphasizes NLP's transformative potential in healthcare, as well as the ethical and technical problems that must be addressed before it can completely fulfill its benefits.
Chapter Preview

Complete Chapter List

Search this Book:
Reset