Cutting-edge Computational Intelligence in Healthcare with Convolution and Kronecker Convolution-based Approaches [Pehme köide]

Section 1: Foundational concepts

1 Introduction to deep learning in medical imaging

2 Fundamentals of convolutional neural networksSection 2: Advanced techniques
in deep learning with kronecker convolutions

3 Kronecker convolutions ensemble vision transformer and 3D kronecker U-net
for volumetric segmentation of kidney stones, cysts and tumor from CT scans

4 Image processing techniques in healthcare for early detection of heart
diseasesSection 3: Applications in medical imaging

5 Automated atypical teratoid /rhabdoid tumor detection in magnetic resonance
imaging using deep learning

6 Ischemic stroke lesion segmentation using multiscale processing and
knowledge distillation through intra-domain teacher

7 Disease classification through advanced neural networksSection 4:
Real-world implementation

8 GAT-Net: ghost attention network for classification of gait-based
neurodegenerative diseases

9 Artificial intelligence-enhanced diagnostics: deep learning in medical
imaging

10 Precision medicine through imaging analytics: Kronecker convolutions in
tumor detection

11 Diagnosis of schizophrenia using convolutional neural networks based on
multichannel electroencephalography signal

12 Detection of anomalies in physiological signals using artificial neural
network

13 Advancements in electrocardiography-based detection of obstructive sleep
apnea: a deep learning approach

14 Machine learning-based life expectancy post chest surgerySection 5: Future
directions and conclusion

15 Challenges and future directions in medical image analysis

Allam Jaya Prakash received the B.Tech. degree in Electronics and Communication Engineering from JNTU Kakinada, India, in 2009, the M.Tech. degree in Digital Electronics and Communication Systems from GMRIT, JNTU Kakinada, India, in 2012, and a PhD degree in Electronics and Communication Engineering from the National Institute of Technology, Rourkela, India, in 2024. He is currently a Postdoctoral Fellow in the Department of Electrical and Communication Engineering at United Arab Emirates University, Al Ain, UAE, and also serves as a Senior Assistant Professor (Grade I) in the School of Computer Science and Engineering at VIT Vellore, India. He has authored more than 30 journal and conference papers in reputable venues, including the IEEE Transactions on Artificial Intelligence, the IEEE Journal of Biomedical and Health Informatics, and Engineering Applications of Artificial Intelligence. His research interests include biomedical signal processing, deep learning, machine learning, edge AI, and remote sensing. He has also served as Guest Editor for a special issue of the IEEE Journal of Biomedical and Health Informatics. He is a regular reviewer for several international journals, including IEEE JBHI, IEEE TIM, IEEE Sensors Journal, IEEE Access, and Biomedical Signal Processing and Control. He was listed among Stanfords Top 2% Scientists in 2024. He can be reached @: [email protected], [email protected].

Kiran Kumar Patro holds ME and PhD degrees from the Department of Electronics and Communication Engineering, Andhra University, Visakhapatnam, India. He first worked as a UGC junior research fellow (Govt. of India) for 2 years and then as a senior research fellow for 3 years at Andhra University. His research interests include biomedical signal processing, image processing, pattern recognition and machine learning. He currently works as an Assistant professor in the Department of Electronics and Communication Engineering, Aditya Institute of Technology and Management. He has published more than 24 papers in refereed international journals. He is an active peer reviewer for reputed journals of IEEE, Elsevier, Springer, Wiley, etc. Pawe Pawiak was born in Ostrowiec, Poland, in 1984. He holds B.Eng. and M.Sc. degrees in Electronics and Telecommunications in 2012, a Ph.D. (with honors) in Biocybernetics and Biomedical Engineering in 2016 from the AGH University of Science and Technology, Krakow, Poland, and a D.Sc. degree in Technical Computer Science and Telecommunications in 2020 from the Silesian University of Technology, Gliwice, Poland. He is the Dean of the Faculty of Computer Science and Mathematics and an Associate Professor at the Cracow University of Technology, Krakow, Poland. He has also served as an Associate Professor at the Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland, and as the Deputy Director for Scientific Affairs at the National Institute of Telecommunications, Warsaw, Poland. He has published more than 100 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 technologies, medicine, biocybernetics, biomedical engineering, and telecommunications.