This volume reviews the convergence of AI and medicine. As healthcare systems face rising demands, clinician shortages, and the complexity of patient data, machine learning and deep learning are stepping in as transformative forces—to improve diagnosis, personalize treatments, and enhance patient outcomes. This book is a comprehensive guide to technologies, applications, and implications of AI in healthcare. It navigates through the foundational principles of machine learning, dives into r...

pAdvanced Explorations in Machine Learning,Computer Vision, and IoT focuses on the convergence ofmachine learningalgorithms,computer visiontechniques, and Internet of Things (IoT) infrastructures to enable scalable, adaptive, and real-time intelligent applications. /ppBalancing strong theoretical foundations with system-level design considerations, the book serves as a structured guide for readers interested in howadvancedmathematical models andlearningparadigms drive modern AI-enabled IoT...

Advanced Explorations in Machine Learning, Computer Vision, and IoT focuses on the convergence of machine learning algorithms, computer vision techniques, and Internet of Things (IoT) infrastructures to enable scalable, adaptive, and real-time intelligent applications.Balancing strong theoretical foundations with system-level design considerations, the book serves as a structured guide for readers interested in how advanced mathematical models and learning paradigms drive modern AI...

Advancements in sensor technology have enabled autonomous systems to operate efficiently and safely in the Internet of Vehicles environment. Multisensor image fusion is a crucial component in enhancing the capabilities of these autonomous systems by combining information from multiple sensors such as cameras, LiDAR, radar, and ultrasonic sensors. This book delves into the role of multisensor image fusion in the Internet of Vehicles for autonomous systems. It will cover the fundamental conc...

The integration ML with robotics and weaponry is revolutionizing mechanical engineering by enabling intelligent systems that can adapt, learn, and operate autonomously. In robotics, ML allows systems to process vast amounts of data from sensors to make real-time decisions. Robots, whether in industrial settings or autonomous vehicles, can navigate environments, recognize objects, and optimize tasks through reinforcement learning algorithms. In military applications, robotics combined with ...

Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep l...

The volume explores a wide-range of applications of computer vision in the field of healthcare. Computer vision, an interdisciplinary field that combines image processing, pattern recognition, and artificial intelligence, has the potential to revolutionize healthcare by enabling automated analysis and interpretation of medical images and videos. This chapter will provide an overview of the current advancements and potential future directions of computer vision applications in healthcare. S...

The book analyzes the combination of intelligent data analytics with the intricacies of biological data that has become a crucial factor for innovation and growth in the fast-changing field of bioinformatics and biomedical systems.Intelligent Data Analytics for Bioinformatics and Biomedical Systems delves into the transformative nature of data analytics for bioinformatics and biomedical research. It offers a thorough examination of advanced techniques, met...

This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation....

The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems.Illustrates the latest technologies in the healthcare domain and the Internet of...

Mining Biomedical Text, Images and Visual Features for Information Retrieval provides the reader with a broad coverage of the concepts, themes, and instrumentalities of the important and evolving area of biomedical text, images, and visual features towards information retrieval. It aims to encourage an even wider adoption of IR methods for assisting in problem-solving and to stimulate research that may lead to additional innovations in this area of research.The book discusses topics such a...

Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigurable architectures like graphic processing units (GPUs), Field programmable gate arrays (FPGAs), or any hybrid system. This great resource will be of interest to researchers working to increase ...