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Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.
The book "Digital Transformation in Healthcare 5.0: Metaverse, Nanorobots, and Machine Learning" is a comprehensive discussion of disruptive technologies and their applications in healthcare. The book starts with an overview of blockchain technology's impact on the healthcare sector, emphasizing its potential to improve data security and interoperability. The book also discusses the Metaverse's role in healthcare transformation, utilizing a blockchain method to improve patient care and medical practices. The book also focuses on the interrelationships of Blockchain-Enabled Metaverse Healthcare Systems and Applications, highlighting innovative strategies. It also introduces an Intraocular Pressure Monitoring System for Glaucoma Patients, demonstrating the integration of IoT and Machine Learning for improved care. The book winds up with a Machine Learning Approach to Voice Analysis in Parkinson's disease Diagnosis, demonstrating the potential of voice analysis as a non-invasive diagnostic tool.
"Sustainability in Healthcare: Advances in mHealth AI and Robotics" explores sustainable methods in the healthcare industry, focusing on rural and community healthcare improvement, the use of robots for sustainability, and the implementation of AI in healthcare. It also explores additive manufacturing, mobile health, biomedical engineering, and telemedicine's role in healthcare sustainability management. The book also discusses the ethical concerns, environmental, social, and economic implications of sustainability in healthcare supply chain management and pandemic management.
This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profitable cloud manufacturing will be gathered to present advanced and specialized research in the selected area.
The goal of this book is to provide a mathematical perspective on some key elements of the so-called deep neural networks (DNNs). Much of the interest in deep learning has focused on the implementation of DNN-based algorithms. Our hope is that this compact textbook will offer a complementary point of view that emphasizes the underlying mathematical ideas. We believe that a more foundational perspective will help to answer important questions that have only received empirical answers so far. The material is based on a one-semester course Introduction to Mathematics of Deep Learning" for senior undergraduate mathematics majors and first year graduate students in mathematics. Our goal is to introduce basic concepts from deep learning in a rigorous mathematical fashion, e.g introduce mathematical definitions of deep neural networks (DNNs), loss functions, the backpropagation algorithm, etc. We attempt to identify for each concept the simplest setting that minimizes technicalities but still contains the key mathematics.
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This book presents research on the state-of-the-art methods and applications. Security and privacy related issues of cloud are addressed with best practices and approaches for secure cloud computing, such as cloud ontology, blockchain, recommender s
This book presents Proceedings of the International Conference on Intelligent Systems and Networks (ICISN 2021), held at Hanoi in Vietnam. It includes peer-reviewed high-quality articles on intelligent system and networks. It brings together professionals and researchers in the area and presents a platform for exchange of ideas and to foster future collaboration. The topics covered in this book include—foundations of computer science; computational intelligence language and speech processing; software engineering software development methods; wireless communications signal processing for communications; electronics track IoT and sensor systems embedded systems; etc.
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