1.

Record Nr.

UNINA9911011348203321

Autore

Kumar Akshi

Titolo

Transformative Natural Language Processing : Bridging Ambiguity in Healthcare, Legal, and Financial Applications / / edited by Akshi Kumar, Saurabh Raj Sangwan

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025

ISBN

3-031-88988-6

Edizione

[1st ed. 2025.]

Descrizione fisica

1 online resource (0 pages)

Altri autori (Persone)

SangwanSaurabh Raj

Disciplina

006.35

Soggetti

Natural language processing (Computer science)

Computational linguistics

Data mining

Artificial intelligence

Data protection

Business - Data processing

Natural Language Processing (NLP)

Computational Linguistics

Data Mining and Knowledge Discovery

Artificial Intelligence

Data and Information Security

Business Informatics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Preface -- 1. Introduction to Natural Language Processing in High-Stakes Domains -- 2. NLP in Medicine: Enhancing Diagnostics and Patient Care -- 3. NLP in the Legal Domain: Ensuring Precision and Compliance -- 4. Introduction to NLP in Finance: Sentiment Analysis and Risk Management -- 5. Managing Uncertainty in NLP: Advanced Techniques and Approaches -- 6. NLP for Fraud Detection and Security in Financial Documents -- 7. Multilingual and Cross-Linguistic Challenges in NLP -- 8. NLP in Action: Case Studies from Healthcare, Finance, and Industry -- 9. Generative Large Language Models in Clinical, Legal and Financial Domains -- 10. Responsible and Ethical AI



in Natural Language Processing.

Sommario/riassunto

The evolving landscape of technology has presented numerous opportunities for addressing some of the most critical challenges in high-stakes domains such as medicine, law, and finance. These fields, where the stakes are exceptionally high, have increasingly turned to Natural Language Processing (NLP) to manage, interpret, and utilize vast amounts of unstructured linguistic data. The complexities and subtleties inherent in human language pose significant challenges in these sectors, where precision and clarity are paramount. Misinterpretation or ambiguity can lead to far-reaching consequences, making the need for advanced NLP techniques crucial. This book aims to bridge the gap between state-of-the-art NLP technologies and their practical applications in medicine, law, and finance. By focusing on the specific challenges and advancements within these sectors, the publication intends to highlight innovative approaches, methodologies, and technologies that are shaping the future of NLP. It discusses the integration of NLP with other technological advancements, the development of new tools and techniques, and the ethical considerations involved in deploying NLP solutions in high-stakes domains. Moreover, the book provides a platform for researchers, practitioners, and industry experts to share their experiences, insights, and research findings. Through comprehensive reviews, case studies, and empirical research, it covers a range of topics including but not limited to handling uncertainty in clinical notes, approaches for dealing with ambiguity in legal documents, sentiment analysis in financial markets, and ethical considerations in the use of NLP for sensitive data.