Generative AI is one of the most trending topics and application in every field of Science and Engineering with AI and Machine Intelligence. It is used to develop new products and automate the system by generating the new and improved models and improve decision making systems.
Generative AI is one of the most trending topics and application in every field of Science and Engineering with AI and Machine Intelligence. It is used to develop new products and automate the system by generating the new and improved models and improve decision making systems.
Debnath Bhattacharyya is a Professor with Computer Science and Engineering Department, Kuala Lumpur University, Vijayawada and Hyderabad Campus, India. He was an Invited International Professor of Lincoln University, Kuala Lumpur, Malaysia. He was the Foreign Professor, Department of Multimedia Engineering, Hannam University, South Korea. Currently, he is the Visiting Professor at University of Johannesburg, South Africa and UCSI University, Kuala Lumpur, Malaysia. He has a Ph.D. (Tech., CSE) from the University of Calcutta, Kolkata. He received his M. Tech (CSE) from West Bengal University of Technology, Kolkata, India. Dr Bhattacharyya is the Senior Member of IEEE, Senior Member of ACM, ACM SIGKDD, OWASP, Life Member of CSI, India, Senior Member of IACSIT, Singapore and Senior Member of IAENG, Hong Kong. He serves as an editor for several reputed journals (indexed by Scopus, SCI, and WoS). He has published 281 Scopus indexed articles and 154 WoS indexed papers. His research interests include Security Engineering, Pattern Recognition, Biometric Authentication, Multimodal Biometric Authentication, Data Mining and Image Processing. He has also published 6 books in Computer Science and Engineering. Yu-Chen Hu has a Ph.D. degree in computer science and information engineering from the Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan. He is a full professor in the Department of Computer Science at Tunghai University, Taichung City, Taiwan. He is a senior member of IEEE and also a member of Computer Vision, Graphics, and Image Processing (CVGIP), the Chinese Cryptology and Information Security Association, and Phi Tau Phi Society of the Republic of China. He serves as editor of Advances in Multimedia (Handiwi), Electronics (MDPI), IET Image Processing, Intelligent Automation & Soft Computing, and Mathematical Problems in Engineering. His interests include image and signal processing, data compression, information hiding, information security, computer network, deep learning, and data engineering.
Inhaltsangabe
Preface. Foundations of Computational Techniques in Healthcare and Drug Discovery: A Deep Learning Perspective. Machine Learning Algorithms and Models for Predictive Healthcare Analytics in Drug Discovery. Computational Intelligence Transforming Healthcare 4.0: Innovations in Medical Image Analysis through AI and IoT Integration. Unlocking Medical Data Intelligence: Methodologies and Practical Applications. Revolutionizing Health Informatics: Artificial Intelligence Applications in Health Care. Empowering Smart Healthcare with Federated Learning: Advancements in Human Health. Precision Prognosis in Oncology: Harnessing Deep Learning for Solid Tumor Imaging. Optimizing Healthcare Decision-Making: Advanced Models for Diverse Applications. Artificial Intelligence-Powered Disease Diagnosis: A New Era in Medical Practice. Cutting-Edge Medical Diagnostics: Identifying Cancerous and Non-Cancerous Tumors with Precision. Harnessing Deep Neural Networks for Human Disease Identification: Insights and Applications. Estimating Disease Severity with Precision: Leveraging Deep Neural Networks. Nodule and Irregular Cell Detection in Organs: Advancements in Medical Imaging. Enhancing Lung Disease Identification Through Ensemble Learning Methods. Unveiling Advanced Techniques for Feature Extraction in Medical Data.
Preface. Foundations of Computational Techniques in Healthcare and Drug Discovery: A Deep Learning Perspective. Machine Learning Algorithms and Models for Predictive Healthcare Analytics in Drug Discovery. Computational Intelligence Transforming Healthcare 4.0: Innovations in Medical Image Analysis through AI and IoT Integration. Unlocking Medical Data Intelligence: Methodologies and Practical Applications. Revolutionizing Health Informatics: Artificial Intelligence Applications in Health Care. Empowering Smart Healthcare with Federated Learning: Advancements in Human Health. Precision Prognosis in Oncology: Harnessing Deep Learning for Solid Tumor Imaging. Optimizing Healthcare Decision-Making: Advanced Models for Diverse Applications. Artificial Intelligence-Powered Disease Diagnosis: A New Era in Medical Practice. Cutting-Edge Medical Diagnostics: Identifying Cancerous and Non-Cancerous Tumors with Precision. Harnessing Deep Neural Networks for Human Disease Identification: Insights and Applications. Estimating Disease Severity with Precision: Leveraging Deep Neural Networks. Nodule and Irregular Cell Detection in Organs: Advancements in Medical Imaging. Enhancing Lung Disease Identification Through Ensemble Learning Methods. Unveiling Advanced Techniques for Feature Extraction in Medical Data.
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