This book uncovers stakes and possibilities offered by Computational Intelligence and Predictive Analytics to Medical Science. The main focus is on data technologies,classification, analysis and mining, information retrieval, and in the algorithms needed to elaborate the informations. A section with use cases and applications follows the two main parts of the book, respectively dedicated to the foundations and techniques of the discipline.

The internet provides a vast amount of data which can be utilised to explore different approaches to solving industry problems. Efficient methods for the retrieval of this information are essential for streamlined business processes. Information Retrieval Methods for Multidisciplinary Applications provides innovative research on information gathering, web data mining, and automation systems. Addressing multidisciplinary applications and focusing on theories and methods with an enterprise-wide perspective, this book is essential for information engineers, scientists, and related professionals.

This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear human lives apart for the passive or provide a cohesive set of opportunities for the knowledgeable to lead and reap the rewards in the evolved knowledge society.

The book also provides in-depth coverage of the functions embedded in modern processors and intelligent communication networks. It focuses on the convergence of the design of modern processor technologies with the switching and routing methodologies of global intelligent networks. Most of the concepts that are generic to the design of terra-flop parallel processors and the terra-bit fiber-optic networks are presented. This book also highlights recent developments in computer and processor technologies into the microscopic and macroscopic medical functions in hospitals and medical centers.
Examination of the latest technologies and innovations presented from academic and industrial perspectives of the concurrent dynamic changes in computer and communication industriesAn up-to-date and coherent perspective of the developments in the wireless and fiber optic network technologies based on the experience and developments in the older copper, cable and hybrid fiber-coaxial communication systemsProvides a set of novel concepts and methodologies for the innovators in industry

"Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines" is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems.

The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELR's completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELR's new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today s big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior.
Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brainOffers a new neuromorphic foundation for machine learning based upon the reduced error logistic regression (RELR) method and provides simple examples of RELR computations in toy problems that can be accessed in spreadsheet workbooks through a companion website"

The growing presence of biologically-inspired processing has caused significant changes in data retrieval. With the ubiquity of these technologies, more effective and streamlined data processing techniques are available. Bio-Inspired Computing for Information Retrieval Applications is a key resource on the latest advances and research regarding current techniques that have evolved from biologically-inspired processes and its application to a variety of problems. Highlighting multidisciplinary studies on data processing, swarm-based clustering, and evolutionary computation, this publication is an ideal reference source for researchers, academics, professionals, students, and practitioners.

In recent years, swarm intelligence has become a popular computational approach among researchers working on optimization problems throughout the globe. Several algorithms inside swarm intelligence have been implemented due to their application to real-world issues and other advantages. A specific procedure, Fireworks Algorithm, is an emerging method that studies the explosion process of fireworks within local areas. Applications of this developing program are undiscovered, and research is necessary for scientists to fully understand the workings of this innovative system. The Handbook of Research on Fireworks Algorithms and Swarm Intelligence is a pivotal reference source that provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm. This book is ideally designed for researchers, data scientists, mathematicians, engineers, software developers, postgraduates, and academicians seeking coverage on this evolutionary computation method.

Recent advances in eye tracking technology will allow for a proliferation of new applications. Improvements in interactive methods using eye movement and gaze control could result in faster and more efficient human computer interfaces, benefitting users with and without disabilities. Gaze Interaction and Applications of Eye Tracking: Advances in Assistive Technologies focuses on interactive communication and control tools based on gaze tracking, including eye typing, computer control, and gaming, with special attention to assistive technologies. For researchers and practitioners interested in the applied use of gaze tracking, the book offers instructions for building a basic eye tracker from off-the-shelf components, gives practical hints on building interactive applications, presents smooth and efficient interaction techniques, and summarizes the results of effective research on cutting edge gaze interaction applications.

Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.

The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security.
very relevant to current research challenges faced in various fieldsself-contained reference to machine learning

emphasis on applications-oriented techniques

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers.
Focuses on the introduction and analysis of key algorithms Includes case studies for real-world applicationsContains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Modern devices, from phones and cars to houses and the appliances within them, are being designed with formidable computational power and expanded functionality. To be truly effective, these smart devices must effectively process data from their environment and experiences and make decisions based on that information. Recent Advances in Ambient Intelligence and Context-Aware Computing investigates the functionality of ubiquitous computational systems and how they may adapt to their environment to improve the quality of interaction for the end-user. This reference book will be of value to under- and post-graduate students, professionals, and researchers networking, computer science, communications, and other information technology disciplines.

Throughout the past decade, the notion of ontologies has influenced research in many application areas including databases, information retrieval, electronic commerce, natural language processing, knowledge management, enterprise systems, systems analysis and design, the Web, and more.Ontology-Based Applications for Enterprise Systems and Knowledge Management provides an opportunity for readers to clearly understand the notion of ontology engineering and the practical aspects of this approach in the domains of two interest areas: Knowledge Management Systems and Enterprise Systems. A perfect reference for researchers, scholars, postgraduate students, and practitioners, this book aims to gather the recent advances and research findings of various topics in ontology use for these application areas.

This book provides a snapshot of the state of current research at the interface between machine learning and healthcare with special emphasis on machine learning projects that are (or are close to) achieving improvement in patient outcomes. The book provides overviews on a range of technologies including detecting artefactual events in vital signs monitoring data; patient physiological monitoring; tracking infectious disease; predicting antibiotic resistance from genomic data; and managing chronic disease. With contributions from an international panel of leading researchers, this book will find a place on the bookshelves of academic and industrial researchers and advanced students working in healthcare technologies, biomedical engineering, and machine learning.

Information in today's advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.

Artificial intelligence is headline news with the launch of the latest ChatGPT and Google Bard. But when did we start making computers mimic the human mind? And what is the reality of the capabilities of AI now, and in the future?

AI has always stirred emotions and caused great excitement and concern. Since the launch of large language models such as ChatGPT, the scope and capabilities of AI look set to transform our technology, in both good and bad ways. AI can help teach us how to write better or help us generate amazing artwork. But in the wrong hands, AI can create fake images and fake information that can be used to damage our societies.

A new addition to the popular Bite-sized Chunks series, this expert-led book will explore how AI has developed from humble beginnings in the 1950s to today’s extraordinary AIs with more neurons than the human brain. Focusing on specific AIs and their creators over the years, it explains the science and engineering behind each AI, discusses ethical issues, and covers all the most fascinating information about one of the most important and contentious developments in human technology (including the latest on generative AI/ChatGPT), as well as what we can expect to see in the future of this field – all in short, accessible bite-sized chunks.

As humans interact more often and more intimately with computers, and as computational systems become an ever more important element of our society, playing roles in education, the production of culture and goods, and management, it is inevitable that we should seek to interact with these systems in ways that take advantage of our powerful emotional capabilities. Creating Synthetic Emotions through Technological and Robotic Advancements compiles progressive research in the emerging and groundbreaking fields of artificial emotions, affective computing, and sociable robotics that allow humans to begin the once impossible-seeming task of interacting with robots, systems, devices, and agents. This landmark volume brings together expert international researchers to expound upon these topics as synthetic emotions move toward becoming a daily reality.

Research on living systems, human level artificial systems, and machines that exhibit intelligent behavioral characteristics is fundamental in order to tackle complex and dynamic issues in nature and create applicable solutions. Investigations into Living Systems, Artificial Life, and Real-World Solutions provides original research on the theoretical and applied aspects of artificial life, as well as addresses scientific, psychological, and social issues of synthetic life-like behavior and abilities. This book is essential for researchers, students, and scientists interested in the emerging discipline of artificial life to further understand and solve real-world problems.

Hybrid Artificial Intelligent Systems (HAIS) try to deal with the complexity of real world phenomena using a multidisciplinary approach and a plurality of techniques. Logistics Management and Optimization through Hybrid Artificial Intelligence Systems offers the latest research within the field of HAIS, surveying the broad topics and collecting case studies, future directions, and cutting edge analyses. Using biologically-inspired algorithms such as ant colony optimization and particle swarm optimization, this text includes solutions and heuristics for practitioners and academics alike, offering a vital resource for staying abreast in this ever-burgeoning field.

This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.