Applied Mathematics for Healthcare Intelligent Systems
Language: English
Published by De Gruyter, 2026
- Hardcover
- New
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
AbeBooks seller since June 11, 1999
Condition: New
£ 137.11
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Seller Inventory # FW-9783112226216
- Title
- Applied Mathematics for Healthcare Intelligent Systems
- Publisher
- De Gruyter
- Publication year
- 2026
- Condition
- New
- Binding
- HRD
- Language
- English
- ISBN 10
- 3112226216
- ISBN 13
- 9783112226216
- Item weight
- 683 grams
This book offers a comprehensive and interdisciplinary perspective on healthcare intelligent systems, highlighting the growing role of applied mathematics, data-driven methodologies, and artificial intelligence in modern healthcare. The book brings together scholarly contributions that explore how intelligent models, data representations, and computational techniques are applied to healthcare diagnostics, medical imaging, and clinical decision-support systems.
The chapters cover a wide range of topics, including medical imaging modalities, data handling and representation, deep learning techniques, explainable and trustworthy artificial intelligence, generative models, three-dimensional reconstruction, performance evaluation metrics, ethical considerations, and emerging trends in healthcare technologies. Through practical insights and real-world case studies, the volume illustrates how intelligent systems support disease detection, diagnosis, and personalized treatment planning.
Designed for researchers, graduate students, and professionals in healthcare technology, computer science, and biomedical engineering, this book serves as a valuable reference on intelligent healthcare solutions.
"Synopsis" may belong to another edition of this title.
About the Author
Dr Monika Sethi is professor in the Department of Computer Science and Engineering at Chitkara University, Punjab, India. She has over 15 years’ experience in the field of teaching and research. Her research interests include Image Processing (ADNI-MRI Images), Deep Learning, Machine Learning, and Wireless Sensor Networks. Her teaching interests include C, C++, Python, Data Structures, Operating Systems, Computer System Architecture, Computer Graphics and Digital Electronics. She has published 28+ research papers in international journals and conferences (Scopus Indexed) and filed 14 patents (9 granted and 5 published). She is a member of the IEI. She holds a PhD degree in “Enhancing the Performance of Convolutional Neural Network for Alzheimer’s disease Classification” from Chitkara University, Punjab and a MTech in (Power Efficient Hierarchical Centralized Routing in WSN) from NIT Hamirpur, India.
Dr Shivani Sood is an assistant professor in the Department of the School of Computer Applications at Lovely Professional University, Phagwara, Punjab, India. Her research interests include Pattern Recognition, Machine Learning, Image Processing, and Data science. Her teaching interests include Python, Java, C/C++, Advanced Data structures, and Data Structure. She has over 7 years of experience in academia, and research. She has filed 2 patents and published 10 articles in international journals and conferences. She holds a Master degree from Sri Sai College of Engineering College, Pathankot. Her specialization includes Advanced Java, Database management skills in their entrepreneurships training . She holds a Ph.D. degree in Computer Science on “Detection and classification of diseases on wheat crop using computer vision and machine learning techniques” in 2023 from Chitkara University (Punjab), India.
Dr Saravjeet Singh has a Ph.D. degree in computer science and engineering. Currently he is working as associate professor in the Department of Computer Science and Engineering at Chitkara University, Punjab, India. He has over 14 years of experience in research, development, and academia. His research interests include offline navigation systems, spatial databases, pattern recognition, mental disorders, and software engineering. He has published 55+ research papers in international journals and conferences (Scopus Indexed) and filed 8 patents.
Arfat Ahmad Khan received the B.Eng. degree in Electrical Engineering from The University of Lahore, Pakistan, in 2013, the M.Eng. degree in Electrical Engineering from the Government College University Lahore, Pakistan, in 2015, and the Ph.D. degree in Telecommunication and Computer Engineering from the Suranaree University of Technology, Thailand, in 2018. From 2014 to 2016, he was an RF Engineer with Etisalat, United Arab Emirates. From 2018 to 2022, he was a Lecturer and a Senior Researcher with the Suranaree University of Technology. He is currently a Senior Lecturer and a Researcher with Khon Kaen University, Thailand. He is rankedamong the world's top 2 percent scientists by Stanford University, USA and Elsevier. He has more 60 high impact factored research publications, where some of his publications are published in top ranked journals including but not limited to IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Transactions on Consumer Electronics, IEEE Transactions on Network Science and Management, IEEE Transactions on Vehicular Technology, Expert System with Applications, Biomedical Signal Processing and Control, CAAI Transactions on Intelligence System. His research interests include Machine, Deep, and Federated Learning for various applications including medical image processing, cyber security, speech recognition, agriculture, healthcare, and advanced wireless communications.
"About the title" may belong to another edition of this title.
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