Smart Medical Imaging for Diagnosis and Treatment Planning -

Smart Medical Imaging for Diagnosis and Treatment Planning

Buch | Hardcover
246 Seiten
2024
Chapman & Hall/CRC (Verlag)
978-1-032-73502-3 (ISBN)
174,55 inkl. MwSt
This book presents advanced research on smart health technologies, focusing upon the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques. It shows how smart health technologies leverage artificial intelligence (AI) and big data analytics.
This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques. It shows how smart health technologies leverage artificial intelligence (AI) and big data analytics to provide more accurate and efficient diagnosis and treatment planning. In search for innovative and novel methods and techniques for health technologies and medical data processing, the book

• Discusses applications of Artificial Intelligence, Data Science, Machine Learning, Deep Learning, the Internet of Things, Big Data, Cloud Computing;

• Includes use of electronic patient records in healthcare, analysis of big data in medical diagnosis, reliability, and challenges of EPR and EHR in smart healthcare;

• Explores evolving techniques for smart healthcare, its application in medical imaging and prediction in the fields of treatment planning;

• Provides recent studies in AI-driven healthcare technologies and medical imaging to outline insight into smart healthcare technologies;

• Discusses the role of big data in smart healthcare, computing techniques for healthcare for medical diagnosis and treatment planning;

• Encompasses the ethical and legal challenges of using smart healthcare and medical data.

This book serves as a valuable reference for researchers working on smart health technologies. Researchers of medical imaging, artificial intelligence, and data science along with healthcare domain will find it a great resource as well.

Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He also holds a position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence , IGI Global, USA. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (SpringerNature), Data-Intensive Research(SpringerNature), Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier). He was an associate editor of IET Image Processing and editorial board member of Complex & Intelligent Systems, Springer Nature. He is an editorial board member of Applied Soft Computing, Elsevier. He is having 35 authored books and over 300 publications in the area of medical imaging, machine learning, computer aided diagnosis, data mining, etc. He is the Fellow of IETE and Senior member of IEEE. Bitan Misra is currently working as an Assistant Professor, in Dept. of CSE, Techno International New Town, Kolkata, India. She received her B. Tech and M. Tech dual degree in Electronics and Telecommunication Engineering from KIIT University, Bhubaneswar, India in 2018. She received her Ph.D. in 2022 from National Institute of Technology, Durgapur, India. She received a Gold Medal during her UG for securing the highest CGPA in the university. She has published almost 15 research papers in various international journals and conferences and has three copyrights. Her main research interests include optimization techniques, deep learning, evolutionary algorithms and soft computing techniques. She has worked as a reviewer in several national and international journals and conferences. She is an Associate Editor of International Journal of Ambient Computing and Intelligence, IGI Global. She is a member of IEEE and Internet Society. Sayan Chakraborty is currently working as a Assistant Professor in the Department of Computer Science and Engineering at the Techno International New Town, West Bengal, India. He has completed his Ph.D. in Image registration from Sikkim Manipal University in the year 2023. He has completed M.Tech from Computer Science & Engineering, JIS College of Engineering. He also completed his B. Tech. from the same college. He has academic experience of 10 years. His research area includes digital image processing, nature inspired algorithms and machine learning. He has about 65 research papers published in international journals, book chapters and conferences on various topics such as optimization, artificial intelligence, pattern recognition and digital image processing. He has 1 book published in Springer. He is an Associate Editor of International Journal of Ambient Computing and Intelligence, IGI Global and Editorial Board member of International Journal of Rough Sets and Data Analysis (IJRSDA) , IGI Global. He is a senior member of IEEE.

Section A: Introduction: 1. Enhancing Intelligent Medical Imaging to Revolutionize Healthcare Section B: Impact of AI in healthcare, medical diagnosis and treatment: 2. Role of AI for Smart Health Diagnosis and Treatment 3. Different Smart Diagnosis Processes of Alzheimer's Brain Disease Using AI Techniques 4. Impact of Artificial Intelligence in Healthcare: Predictors of Multiple Sclerosis Section C: Medical imaging technologies and their applications in diagnosis and treatment: 5. Enhancing Patient Care with Modality-Based Image Registration in Modern Healthcare 6. Fashionable and disposable electrochemical sensors as modern healthcare appliance Section D: Infectious diseases detection and treatment planning: 7. Smart healthcare systems in combating infectious diseases outbreaks 8. Facemask and Handgloves Detection using Hybrid Deep Learning Model Section E: Machine learning in medical diagnosis and treatment planning: 9. Utilization of Machine Learning and Deep Learning Classifiers in Predicting Users’ Performance in Augmented Reality Surgical Environments: A Comparative Analysis Section F: Use and regulation of digital health technologies in healthcare: 10.The Future of Medical Imaging: Ensuring Ethical and Legal Compliance.

Erscheinungsdatum
Zusatzinfo 21 Tables, black and white; 41 Line drawings, black and white; 6 Halftones, black and white; 47 Illustrations, black and white
Sprache englisch
Maße 156 x 234 mm
Gewicht 635 g
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Informatik Software Entwicklung
Medizin / Pharmazie Medizinische Fachgebiete Radiologie / Bildgebende Verfahren
Studium 2. Studienabschnitt (Klinik) Anamnese / Körperliche Untersuchung
Recht / Steuern Privatrecht / Bürgerliches Recht IT-Recht
ISBN-10 1-032-73502-3 / 1032735023
ISBN-13 978-1-032-73502-3 / 9781032735023
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
Neurographie, Myographie, Evozierte Potenziale und EEG

von Volker Milnik

Buch | Softcover (2024)
Urban & Fischer in Elsevier (Verlag)
58,00
aus Klinik und Praxis

von Torben Pottgießer; Stefanie Ophoven; Elisabeth Schorb

Buch | Softcover (2023)
Urban & Fischer (Verlag)
42,00