Name: Natural Language Processing for Healthcare. The Rise of Intelligent Assistants
Price: 3381.03 MXN
Availability: InStock
Author: Kamal, PhD , Delhi-NCR Ghaziabad, Uttar Pradesh, India) Upreti;Shubham, PhD Mahajan;Laxmi, PhD Shaw
ISBN: 9780443452529

portada Natural Language Processing for Healthcare. The Rise of Intelligent Assistants

Natural Language Processing for Healthcare. The Rise of Intelligent Assistants

Formato

Libro Físico

Editorial

Academic Press Inc

Autor

Kamal, PhD , Delhi-NCR Ghaziabad, Uttar Pradesh, India) Upreti;Shubham, PhD Mahajan;Laxmi, PhD Shaw

Colección

Advances in ubiquitous sensing applications for healthcare

Año

2026

N° páginas

400

Encuadernación

Tapa Blanda

Dimensiones

23.50 x 19.10 cm

ISBN13

9780443452529

Natural Language Processing for Healthcare. The Rise of Intelligent Assistants

Kamal, Phd , Delhi-Ncr Ghaziabad, Uttar Pradesh, India) Upreti;Shubham, Phd Mahajan;Laxmi, Phd Shaw (Autor) · Academic Press Inc · Tapa Blanda

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Reseña del libro "Natural Language Processing for Healthcare. The Rise of Intelligent Assistants"

Natural Language Processing for Healthcare: The Rise of Intelligent Assistants addresses the critical gap between cutting-edge AI research and its practical application in healthcare, offering an accessible yet comprehensive guide tailored to the unique challenges of medical environments. It highlights how NLP technologies are revolutionizing patient care, medical documentation, and clinical decision-making, while emphasizing ethical, legal, and interoperability considerations. Structured into four sections, the book begins by laying foundational knowledge in NLP and healthcare data, covering crucial concepts such as tokenization, medical ontologies like UMLS and SNOMED CT, machine learning models including BioBERT and ClinicalBERT, and the emerging impact of large language models like GPT. The applications section explores real-world implementations of intelligent assistants, such as virtual health chatbots, clinical documentation tools, conversational AI for patient engagement, and voice recognition integrated into electronic health records. Technical chapters provide insights into system architectures, evaluation metrics, data privacy, security, and interoperability standards like FHIR. The final section looks ahead to future directions including multilingual NLP, federated learning for privacy preservation, and the evolving landscape of AI-driven healthcare assistants. This book is an indispensable resource for a broad audience. Healthcare professionals and clinicians will find practical insights into streamlining patient care and diagnostics. Biomedical researchers and data scientists can deepen their understanding of NLP methods tailored to medical data. Students, educators, technology developers, and healthcare administrators alike will benefit from the book’s balanced coverage of theory, implementation, and regulation, empowering them to innovate and responsibly deploy intelligent assistants that enhance healthcare delivery worldwide.