£74.99
£74.99
This book explores how deep learning AI can solve healthcare’s challenges with fragmented data and security. It covers diverse applications from disease detection to EHR management and telemedicine, offering cutting-edge insights for researchers, practitioners, and policymakers.
Healthcare faces significant challenges due to fragmented data, vendor-locked systems, and security concerns, which hinder the timely delivery of clinical insights and efficient workflow management. This book explores the transformative potential of AI, particularly deep learning (DL) AI, in addressing these issues and enabling personalized healthcare. It covers diverse applications such as clinical trials, telemedicine, EHR management, and disease detection, emphasizing the importance of accurate algorithms to enhance patient outcomes. Key chapters delve into AI’s impact on areas like Parkinson’s and Alzheimer’s detection, the role of blockchain in data integrity, the use of NLP, AR/VR in healthcare, and strategies to combat billing fraud. The book also highlights the importance of diversity in healthcare and presents cutting-edge DL frameworks, such as YOLOv8 and U-Net, for medical image segmentation, offering valuable insights for researchers, practitioners, and policymakers alike.
This book explores the latest research in education design for virtual and augmented reality. Using numerous studies and examples, it will help the reader gain a better understanding of the nature of these realities and their applications in theory and practice.
This book shows how artificial intelligence (AI) and machine learning (ML) are used to prevent security assaults on blockchain. It explores use cases and security methods, arguing that integrating AI and ML is crucial for increasing blockchain security.
This multidisciplinary book explores COVID-19’s impact across the sciences and humanities. It offers varied perspectives on the pandemic’s challenges and solutions, with a specific focus on Indonesia. For researchers, students, the public, and policy makers.
Satellite images often suffer from interpretability issues and lost details due to sensor limitations. This book exploits deep learning to boost minute details and improve classification, showing how super-resolution improves spatial detail for precise decision-making.
This volume presents research merging classical measurement theory with modern data science. Discover novel methods for superior measurement design, robust data evaluation, and efficient instrumentation implementations.
This book offers an integral view of human speech behavior, uniting biology, linguistics, math, and AI. It explores neural networks and microelectronics for speech recognition, text-to-speech synthesis, and dialogue systems. For a broad professional audience.
This book explores how artificial intelligence (AI) interprets behavioral patterns and their influence on personality. It discusses AI’s uses, from controlling diseases to modern personality analysis, and its challenges. Perfect for data scientists, academics, and students.
Using real-world cases, this book illustrates how to handle volatile financial time series data. Learn to apply statistical, machine learning, and deep learning techniques with R and Python to build robust predictive models and construct profitable investment portfolios.
This book explores artificial intelligence through the unique lens of art, showing how we can engage with AI without being subjugated by it. Each chapter begins with a work of art to guide the reader through philosophical keywords like “author,” “memory,” and “human.”
This book is a precise and comprehensive history of the digital computer, tracing its roots and routes through the modern era. Though dealing with the history of technology in general, its central focus is the automatic digital program-controlled calculating devices of 1935-1945.
