Natural Language Processing for Healthcare
The Rise of Intelligent Assistants
- 1st Edition - March 27, 2026
- Latest edition
- Editors: Laxmi Shaw, Shubham Mahajan, Kamal Upreti
- Language: English
Natural Language Processing for Healthcare: The Rise of Intelligent Assistants addresses the critical gap between cutting-edge AI research and its practical applications in health… Read more
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.
- Bridges AI research and healthcare practice with accessible, healthcare-focused NLP insights for clinical and operational use
- Provides practical guidance on designing and deploying intelligent virtual assistants to enhance patient care and engagement
- Addresses ethical, legal, and interoperability challenges unique to healthcare NLP applications
- Explores cutting-edge technologies, including large language models and federated learning in real-world medical contexts
- Equips data scientists and clinicians with tools to analyze unstructured medical data and improve clinical decision-making
1. The Digital Health Revolution: Natural Language Processing Technologies Reshaping Patient Care and Medical Documentation
2. Large Language Models and Generative AI in Healthcare: Multimodal Intelligence, Clinical Integration, and the Future of Medical Practice
3. Navigating the Utility of Generative Artificial Intelligence in Healthcare Delivery
4. GENERATIVE ARTIFICIAL INTELLIGENCE IN MEDICINE
Section II: Core Technologies and Approaches
5. Advancing Patient Care with Conversational AI: Applications, Challenges, and Future Directions
6. The Voice Revolution in Medicine: Reshaping Clinical Workflows with Voice Assistants and Speech Recognition
7. MACHINES THAT UNDERSTAND ILLNESS: Natural Language Processing based hospital kiosk systems
8. Telehealth Workspaces for Healthcare Providers
Section III: Applications and Case Studies
9. AI-Driven Innovations in Infectious Disease Detection and Control
10. Depression Identification from Social Media using n-gram based Deep Neural Network
11. HeaLytix: Comparative Analysis of Classification Algorithms and Deep Learning Optimizers For Cardiac Disease Detection
12. 3D U-Net based Segmentation of Liver Vessels from Computed Tomography Images
13. Revolutionizing Patient Care with Digital Twins: A Smart Healthcare Perspective
Section IV: Global, Ethical, and Technical Challenges
14. Legal And Regulatory Compliance In Digital Twin - Enabled Healthcare
15. Multilingual NLP, Personalisation, and Global Health
16. AI for Multilingual, Human Centered Personalization, and Public Health
17. Data Privacy, Security, and Ethics in Medical NLP
18. Federated Learning, Explainability, and the Road Ahead
- Edition: 1
- Latest edition
- Published: March 27, 2026
- Language: English
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Laxmi Shaw
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.
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Shubham Mahajan
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.
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Kamal Upreti
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.