CyberMedics: Navigating AI and Security in the Medical Field is a comprehensive exploration of the transformative role of artificial intelligence (AI) in healthcare and the critical importance of securing medical data in an increasingly digital world. As AI technologies revolutionize diagnostics, treatment planning, and patient care, they also introduce new challenges related to data privacy, ethical considerations, and cybersecurity. This book offers a balanced perspective, providing healthcare professionals, technologists, and policymakers with the tools they need to understand and navigate the intersection of AI and security. Through detailed case studies, expert insights, and practical guidance, readers will discover how AI can be leveraged to improve patient outcomes while maintaining the highest standards of data protection.
Key topics include:
AI in healthcare, exploring how emerging technologies like machine learning, natural language processing, and predictive analytics are poised to reshape the industry
the ethical implications of AI in healthcare
strategies for safeguarding sensitive information against cyber threats
future frameworks governing the use of AI in medical settings
Whether you're on the front lines of patient care, involved in healthcare IT, or shaping policy, CyberMedics: Navigating AI and Security in the Medical Field equips you with the knowledge to make informed decisions in a rapidly evolving landscape, ensuring that innovation and security go hand in hand to enhance the quality of care.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Academic, Postgraduate, and Professional Reference
Illustrationen
43 s/w Zeichnungen, 12 s/w Tabellen, 48 s/w Abbildungen, 5 s/w Photographien bzw. Rasterbilder
12 Tables, black and white; 43 Line drawings, black and white; 5 Halftones, black and white; 48 Illustrations, black and white
Maße
Höhe: 240 mm
Breite: 161 mm
Dicke: 15 mm
Gewicht
ISBN-13
978-1-032-84702-3 (9781032847023)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr Varun Sapra is presently associated as Associate Professor with the School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India. He is an accomplished academic professional with 18 years of experience in both academia and industry. Holding a Ph.D. in Computer Science, he brings a wealth of expertise to his teaching and research endeavours. He has to his credit more than 40 research papers in peer-reviewed International Journals & Conferences, 2 patents grant and several copyrights & edited books, and chapters in international journals and publishers.
Dr Rohit Tanwar received his bachelor's degree (B.Tech) in CSE from Kurukshetra University, Kurukshetra, India, and master's degree (M.Tech) in CSE from YMCA University of Science and Technology, Faridabad, India. Dr. Tanwar was awarded his Ph.D. degree in the year 2019 from Kurukshetra University. He has more than 13 years of experience in teaching. Currently, he is working as Senior Associate Professor in School of Computer Science, UPES Dehradun. His areas of interests include Network Security, Optimization Techniques, Internet of Things, Healthcare, Wireless Sensor Networks, etcHe has been associated with many conferences throughout India as TPC member and session chair.
Dr. Tanwar has published more than 50 research papers in different journals of international repute. He has 7 books and 6 patents to his credit. He is a senior IEEE member and Senior EAI member. He is listed as editorial board review member in different SCI and Scopus Indexed Journals. Dr. Tanwar has supervised many PG and Ph.D. students in field of network security. He is an active reviewer of various projects that are submitted to UGC for funding.
Dr Luxmi Sapra is working as Associate Professor at Graphic Era Hill University, Dehradun, India. She has done her Doctorate in Computer Science and Engineering from NorthCap University and received her Master's in Technology from MDU, Rohtak. India. She has approximately 18 years of research and teaching experience. She has to her credit more than 40 publications in reputed journals and conferences including Elsevier, Springer and IEEE. She is also a reviewer of various international Journals. She has also received 3AI Pinnacle Award for Women in AI and Analytics in 2020. Awarded 4th Himalayi Nari Shakti Samman-2022 on the occasion of Women's day 8th March 2022 at DIT University, Dehradun. Her research areas include Cyber Security, Machine Learning, Artificial Intelligence and Healthcare. She has published five patents and chaired sessions in International conferences.
Herausgeber*in
University of Petroleum and Energy Studies
Dev Bhoomi Uttarakhand University
About the Editors. List of Contributors. Chapter 1: Enhancing Energy Efficiency and Safety in Smart Homes: A Framework for Secure IoT-Driven Home Automation with Facial Recognition and Sensor Networks. Chapter 2: Embracing the Future: Tracing the Role of Artificial Intelligence (AI) and Internet of Things (IoT) in Secure Agricultural Automation. Chapter 3: Enhancing Face Recognition Accuracy in Authentication Systems through Hyperparameter Tuning of Deep Learning Model. Chapter 4: Neuromorphic Horizons: Exploring the Intersection of Generative AI and Brain-Inspired Computing in Secured Healthcare. Chapter 5: Improving Pneumonia Diagnosis Correctness with the Synergistic Approach using Swin Transformer and Deep Learning Architectures on Chest X-Ray Images. Chapter 6: The Future of Healthcare Security: AI and Cyber Defenses. Chapter 7: An Efficient Machine Learning Approach to Mitigate DDoS Attack in Ad-hoc Network. Chapter 8: Role of Artificial Intelligence in Healthcare. Chapter 9: Intentions in the Digital Age: Paving the Path to Sustainable Online Insurance. Chapter 10: Enhancing Anatomical Education through Artificial Intelligence: Integrating Security and Ethical Dimensions - A Comprehensive Review. Chapter 11: A Comprehensive Exploration of Sentiment Analysis Methods for Social Media Data using Python. Index.
