
Cutting-edge Computational Intelligence in Healthcare with Convolution and Kronecker Convolution-based Approaches
- 1st Edition - January 1, 2026
- Imprint: Academic Press
- Editors: Pawel Plawiak, Allam Jaya Prakash, Kiran Kumar Patro
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 3 0 8 2 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 3 0 8 3 - 4
Cutting-edge Computational Intelligence in Healthcare with Convolution and Kronecker Convolution-based Approaches focuses on the use of deep learning techniques in the field of med… Read more
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- Investigates opportunities and challenges of deep learning, including convolutional neural networks (CNNs) and their applications in medical image processing
- Includes comprehensive examination and elucidation of Kronecker convolutional procedures and their significance in medical image processing
- Explores specific medical imaging tasks where Kronecker convolutions prove beneficial
- Provides detailed examples demonstrating how convolutions may be employed to improve healthcare, offering insights into how deep learning is currently being used in clinical settings
1. Introduction to Deep Learning in Medical Imaging
2. Fundamentals of Convolutional Neural Networks
Section 2. Advanced Techniques in Deep Learning with Kronecker Convolutions
3. Kronecker Convolutions: A Deep Dive
4. Image Processing Techniques in Healthcare
Section 3. Applications in Medical Imaging
5. Kronecker Convolutions in Tumor Detection
6. Enhancing Organ Segmentation with Deep Learning
7. Disease Classification through Advanced Neural Networks
Section 4. Real-World Implementation
8. AI-Driven Diagnostic Imaging
9. Precision Medicine through Imaging Analytics
10. Wearable Devices and Continuous Monitoring
Section 5. Future Directions and Conclusion
11. Challenges and Future Directions in Medical Image Analysis
12. Conclusion and Future Trends
- Edition: 1
- Published: January 1, 2026
- Imprint: Academic Press
- Language: English
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Pawel Plawiak
Paweł Pławiak was born in Ostrowiec, Poland, in 1984. He holds BEng and MSc degrees in electronics and telecommunications, a PhD (honors) in biocybernetics and biomedical engineering from the AGH University of Science and Technology, Cracow, Poland, and a DSc degree in technical computer science and telecommunications from Silesian Technical University, Gliwice, Poland. He is the Head of Department of Information and Communications Technology and an Associate Professor in Cracow University of Technology, Krakow, and Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice. He has published more than 70 papers in refereed international SCI-IF journals. His research interests include machine learning and computational intelligence (e.g., artificial neural networks, genetic algorithms, fuzzy systems, support vector machines, k-nearest neighbours, and hybrid systems), ensemble learning, deep learning, evolutionary computation, classification, pattern recognition, signal processing and analysis, data analysis and data mining, sensor techniques, medicine, biocybernetics, biomedical engineering and telecommunications.
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Allam Jaya Prakash
Allam Jaya Prakash was born in Venkampeta (Village), Parvatipuram (District), Andhra Pradesh, India, in 1988. He received a BTech degree in electronics and communication engineering from GITAS, Piridi, affiliated to Jawaharlal Nehru Technological University Kakinada (JNTUK), India, in 2009, and an MTech degree in digital electronics and communication systems from the GMRIT, Rajam, affiliated to Jawaharlal Nehru Technological University Kakinada (JN TUK), in 2012. He completed his Ph.D. (Artificial Intelligence) from NIT Rourkela, Rourkela, Odisha, India. Presently he is working as Senior Assistant Professor in the School of Computing Science and Engineering (SCOPE), VIT Vellore, India. His current area of research includes biomedical signal processing, machine learning, and deep learning techniques.
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