Natural Language Processing for Healthcare: The Rise of Intelligent Assistants - Brossura

Brossura

ISBN 10: 0443452520 ISBN 13: 9780443452529

Casa editrice: Academic Press, 2026

Riassunto

Natural Language Processing for Healthcare: The Rise of Intelligent Assistants addresses the critical gap between cutting-edge AI research and its practical applications in healthcare, offering an accessible 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 concepts such as tokenization, medical ontologies like UMLS and SNOMED CT, machine learning models, including BioBERT and ClinicalBERT, and emerging impacts 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.

Su questo libro

Informazioni sugli autori

Dr. Laxmi Shaw is a Postdoctoral Scholar at Texas State University, specializing in adversarial machine learning, large language models, and healthcare fraud analytics. She previously volunteered as a Senior Postdoctoral Researcher at UT Austin’s Dell Medical School, focusing on predictive biomarker modeling and inflammation detection using HPC. With over six years of industry and research experience at Samsung R&D and Carrier Corporation, her expertise includes AI-driven product development, IoT analytics, and digital twin modeling.

She earned her Ph.D. in Electrical Engineering with a specialization in Artificial Intelligence and Machine Learning from the prestigious Indian Institute of Technology (IIT) Kharagpur, India. She also holds a Master of Technology (M.Tech) in Instrumentation and Electronics Engineering from Jadavpur University, and a Bachelor of Engineering (B.E.) in Electronics and Instrumentation Engineering from Sambalpur University, Odisha. She has authored three books and over 35 peer-reviewed papers on AI/ML security, EEG processing, IoT anomaly detection, and GPU-accelerated healthcare analytics. A Senior IEEE member and award-winning researcher, she actively reviews for leading journals and is committed to ethical, explainable, and secure AI, especially in healthcare and adversarial contexts.

Dr. Shubham Mahajan is a respected academic and researcher, and a member of well-known professional organizations like IEEE, ACM, and IAENG. He completed his B.Tech. from Baba Ghulam Shah Badshah University, his M.Tech. from Chandigarh University, and his Ph.D. from Shri Mata Vaishno Devi University (SMVDU), Katra. He is currently working as an Assistant Professor at Amity University, Haryana.

Dr. Mahajan has made strong contributions in the fields of artificial intelligence and image processing. He holds nineteen Indian patents, along with one Australian and one German patent. He has published more than 103 research papers in national and international journals and conferences, including 55 in SCIE journals and 48 indexed by Scopus. He has also edited 10 Scopus-indexed books. His research areas include image processing, video compression, image segmentation, fuzzy entropy, nature-inspired algorithms, optimization, data mining, machine learning, robotics, and optical communication. He won the Best Research Paper Award at ICRIC 2019 (Springer LNEE series).

Throughout his career, Dr. Mahajan has received many awards, such as the Best Student Award (2019), IEEE Region-10 Travel Grant (2019), 2nd runner-up in IEEE RAS Hackathon (2019, Bangladesh), IEEE SERCF (2020), Emerging Scientist Award (2021), and the IEEE SPS Professional Development Grant (2021). He also received the Excellence in Research Award in 2023.

Beyond research, Dr. Mahajan has contributed to the academic community in many ways. He has worked as a Campus Ambassador for IEEE at top institutions like IIT Bombay, IIT Kanpur, IIT Varanasi, and IIT Delhi, as well as for several multinational companies. He is active in promoting international research collaborations and serves on Technical Program Committees and Editorial Boards of various international conferences and journals.

Dr. Kamal Upreti is an Associate Professor in the Department of Computer Science at CHRIST (Deemed to be University), Delhi NCR, Ghaziabad, India. He holds a B.Tech (Hons) from UPTU, an M.Tech (Gold Medalist), a PGDM (Executive) from IMT Ghaziabad, a Ph.D. in Computer Science & Engineering, and completed a postdoc at National Taipei University of Business, Taiwan, funded by MHRD.

With over 15 years of teaching, research, and corporate experience, Dr. Upreti has published 50+ patents, 32 magazine issues, 110+ research papers, and authored or edited 45+ books with publishers like CRC Press and Oxford. His expertise spans modern physics, data analytics, cybersecurity, machine learning, healthcare, embedded systems, and cloud computing.

He has worked with organizations including HCL, NECHCL, Hindustan Times, and various academic institutes. Notable projects include Japan’s “Hydrastore,” India’s Integrated Power Development Scheme (IPDS), and a significant ICMR-funded cardiovascular disease prediction project (₹80 Lakhs) in collaboration with GB Pant and AIIMS Delhi. He has secured funding from DST SERB (₹5 Lakhs) for ICSCPS-2024 and AICTE-IBIP (₹10 Lakhs) for 2024-2026.

Dr. Upreti frequently serves as a session chair, keynote speaker, corporate trainer, and faculty developer. He has been honored as Best Teacher, Best Researcher, and Gold Medalist in his M.Tech program.

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Academic Press
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 0443452520
• ISBN 13: 9780443452529
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 442
• Redattore: Shaw
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile