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Artificial Intelligence in Healthcare and Medicine
by Kayvan NajarianThis book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.
Artificial Intelligence in Label-free Microscopy: Biological Cell Classification by Time Stretch
by Ata Mahjoubfar Claire Lifan Chen Bahram JalaliThis book introduces time-stretch quantitative phase imaging (TS-QPI), a high-throughput label-free imaging flow cytometer developed for big data acquisition and analysis in phenotypic screening. TS-QPI is able to capture quantitative optical phase and intensity images simultaneously, enabling high-content cell analysis, cancer diagnostics, personalized genomics, and drug development. The authors also demonstrate a complete machine learning pipeline that performs optical phase measurement, image processing, feature extraction, and classification, enabling high-throughput quantitative imaging that achieves record high accuracy in label -free cellular phenotypic screening and opens up a new path to data-driven diagnosis.
Artificial Intelligence in Medical Imaging: From Theory to Clinical Practice
by Lia Morra Silvia Delsanto Loredana CorrealeChoice Recommended Title, January 2021 This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective
Artificial Intelligence in Medical Imaging Technology: An Introduction
by Euclid Seeram Vijay KanadeThis book covers the principles, concepts, and applications of artificial intelligence in medical imaging technologies, specifically in the context of diagnostic imaging, such as radiography and radiological technology. First, artificial intelligence and its subsets machine learning and deep learning are described followed by a discussion of applications of these AI principles in medical imaging technologies. Finally, ethical questions, regulatory aspects, and future trends and challenges are also reviewed in this textbook. This book is intended for both students and practitioners in radiological technology, radiography, radiation therapy, nuclear medicine technology, diagnostic medical sonography, and biomedical engineering technology. Furthermore, residents in radiology, and medical physics students and related healthcare personnel (administrators and managers for example) may find this book useful.
Artificial Intelligence in Medicine
by Hutan Ashrafian Niklas LidströmerThis book provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting. Artificial Intelligence in Medicine aims to give readers the required knowledge to apply artificial intelligence to clinical practice. The book is relevant to medical students, specialist doctors, and researchers whose work will be affected by artificial intelligence.
Artificial Intelligence in Medicine: Applications, Limitations and Future Directions
by Manda Raz Tam C. Nguyen Erwin LohThis book identifies Artificial Intelligence (AI) as a growing field that is being incorporated into many aspects of human life, including healthcare practice and delivery. The precision, automation, and potential of AI brings multiple benefits to the way disease is diagnosed, investigated and treated. Currently, there is a lack of any appreciable understanding of AI and this book provides detailed understandings, which include; foundational concepts, current applications, future challenges amongst most healthcare practitioners. The book is divided into four sections: basic concepts, current applications, limitations and future directions. Each section is comprised of chapters written by expert academics, researchers and practitioners at the intersection between AI and medicine. The purpose of the book is to promote AI literacy as an important component of modern medical practice. This book is suited for all readers as it requires no previous knowledge, it walks non-technical clinicians through the complex ideas and concepts in an easy to understand manner.
Artificial Intelligence in Medicine
by Thompson StephanIn the ever-evolving realm of healthcare, Artificial Intelligence in Medicine emerges as a trailblazing guide, offering an extensive exploration of the transformative power of Artificial Intelligence (AI). Crafted by leading experts in the field, this book sets out to bridge the gap between theoretical understanding and practical application, presenting a comprehensive journey through the foundational principles, cutting-edge applications, and the potential impact of AI in the medical landscape.This book embarks on a journey from foundational principles to advanced applications, presenting a holistic perspective on the integration of AI into diverse aspects of medicine. With a clear aim to cater to both researchers and practitioners, the scope extends from fundamental AI techniques to their innovative applications in disease detection, prediction, and patient care.Distinguished by its practical orientation, each chapter presents actionable workflows, making theoretical concepts directly applicable to real-world medical scenarios. This unique approach sets the book apart, making it an invaluable resource for learners and practitioners alike.Key Features:• Comprehensive Exploration: From deep learning approaches for cardiac arrhythmia to advanced algorithms for ocular disease detection, the book provides an in-depth exploration of critical topics, ensuring a thorough understanding of AI in medicine.• Cutting-Edge Applications: The book delves into cutting-edge applications, including a vision transformer-based approach for brain tumor detection, early diagnosis of skin cancer, and a deep learning-based model for early detection of COVID-19 using chest X-ray images.• Practical Insights: Practical workflows and demonstrations guide readers through the application of AI techniques in real-world medical scenarios, offering insights that transcend theoretical boundaries.This book caters to researchers, practitioners, and students in medicine, computer science, and healthcare technology. With a focus on practical applications, this book is an essential guide for navigating the dynamic intersection of AI and medicine. Whether you are an expert or a newcomer to the field, this comprehensive volume provides a roadmap to the revolutionary impact of AI on the future of healthcare.
Artificial Intelligence in PET/CT Oncologic Imaging
by John A. Andreou Paris A. Kosmidis Athanasios D. GouliamosThis book presents artificial intelligence applications that may help in detecting disease, defining tissue characterization (benign vs malignant), staging and correlation with molecular biomarkers. Originally positioned as a means for noninvasive molecular phenotyping and quantification in the 1970s, PET's technological improvements in the 2000s generated renewed interest in quantification, which has grown over the last five years. This progress is parallel with the development of Artificial intelligence (AI) systems for Oncology which aim at providing the best possible treatment to patients suffering from lung, breast, brain, prostate, liver and other types of cancer. The chapters provide an overview of the use of AI in PET/CT imaging for various types of cancer, and it will be an invaluable tool especially for nuclear medicine physicians and oncologists.
Artificial Intelligence in Process Fault Diagnosis: Methods for Plant Surveillance
by Richard J. FickelschererArtificial Intelligence in Process Fault Diagnosis A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, i.e., computer programs capable of analyzing process plant operations to identify faults, improve safety, and enhance productivity. Prohibitive cost and challenges of application have prevented widespread industry adoption of this technology, but recent advances in artificial intelligence promise to place these programs at the center of manufacturing process analysis. Artificial Intelligence in Process Fault Diagnosis brings together insights from data science and machine learning to deliver an effective introduction to these advances and their potential applications. Balancing theory and practice, it walks readers through the process of choosing an ideal diagnostic methodology and the creation of intelligent computer programs. The result promises to place readers at the forefront of this revolution in manufacturing. Artificial Intelligence in Process Fault Diagnosis readers will also find: Coverage of various AI-based diagnostic methodologies elaborated by leading expertsGuidance for creating programs that can prevent catastrophic operating disasters, reduce downtime after emergency process shutdowns, and moreComprehensive overview of optimized best practices Artificial Intelligence in Process Fault Diagnosis is ideal for process control engineers, operating engineers working with processing industrial plants, and plant managers and operators throughout the various process industries.
Artificial Intelligence in Radiation Oncology and Biomedical Physics (Imaging in Medical Diagnosis and Therapy)
by Gilmer Valdes Lei XingThis pioneering book explores how machine learning and other AI techniques impact millions of cancer patients who benefit from ionizing radiation. It features contributions from global researchers and clinicians, focusing on the clinical applications of machine learning for medical physics. AI and machine learning have attracted much recent attention and are being increasingly adopted in medicine, with many clinical components and commercial software including aspects of machine learning integration. General principles and important techniques in machine learning are introduced, followed by discussion of clinical applications, particularly in radiomics, outcome prediction, registration and segmentation, treatment planning, quality assurance, image processing, and clinical decision-making. Finally, a futuristic look at the role of AI in radiation oncology is provided. This book brings medical physicists and radiation oncologists up to date with the most novel applications of machine learning to medical physics. Practitioners will appreciate the insightful discussions and detailed descriptions in each chapter. Its emphasis on clinical applications reaches a wide audience within the medical physics profession.
Artificial Intelligence, Learning and Computation in Economics and Finance (Understanding Complex Systems)
by Ragupathy VenkatachalamThis book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded.Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools.The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.
Artificial Intelligence Models for the Dark Universe: Forays in Mathematical Cosmology
by Ariel FernándezThe dark universe contains matter and energy unidentifiable with current physical models, accounting for 95% of all the matter and energetic equivalent in the universe. The enormous surplus brings up daunting enigmas, such as the cosmological constant problem and the apparent distortions in the dynamics of deep space, and so coming to grips with the invisible universe has become a scientific imperative.This book addresses this need, reckoning that no cogent physical model of the dark universe can be implemented without first addressing the metaphysical hurdles along the way. The foremost problem is identifying the topology of the universe which, as argued in the book, is highly relevant to unveil the secrets of the dark universe.Artificial Intelligence (AI) is a valuable tool in this effort since it can reconcile conflicting data from deep space with the extant laws of physics by building models to decipher the dark universe. This book explores the applications of AI and how it can be used to embark on a metaphysical quest to identify the topology of the universe as a prerequisite to implement a physical model of the dark sector that enables a meaningful extrapolation into the visibile sector.The book is intended for a broad readership, but a background in college-level physics and computer science is essential. The book will be a valuable guide for graduate students as well as researchers in physics, astrophysics, and computer science focusing on AI applications to elucidate the nature of the dark universe.Key Features:· Provides readers with an intellectual toolbox to understand physical arguments on dark matter and energy.· Up to date with the latest cutting-edge research.· Authored by an expert on artificial intelligence and mathematical physics.
Artificial Intelligence of Things for Achieving Sustainable Development Goals (Lecture Notes on Data Engineering and Communications Technologies #192)
by Sanjay Misra Kerstin Siakas Georgios LampropoulosThis book covers various topics and trends regarding Artificial Intelligence (AI), Internet of Things (IoT), and their applications in society, industry, and environment for achieving Sustainable Development Goals (SDGs) suggested by the United Nations. Additionally, it discusses their advancements and fusion as well as the realization of Artificial Intelligence of Things (AIoT). The book aims to provide an overview and recent research into the fusion, integration, advancements, and impact of these technologies in the context of SDGs achievement. The topics include the applications of AI, IoT, big data, AI-based and IoT-based cloud computing, machine learning and deep learning techniques, and blockchain among others for achieving SDGs. It also presents findings and discussions on potential application domains, addresses open issues and challenges, offers solutions, and provides suggestions for future research for achieving SDGs. The chapters are clustered, according to particular SDGsor areas of focus, into: i) the realization of AIoT for SDGs, ii) the role of AIoT in achieving society and wellbeing-related SDGs, iii) the fulfillment of industrial sectors, infrastructure, and economy-related SDGs through AIoT, and iv) the use of AIoT to aid natural resources and environment-related SDGs. The book assists researchers, practitioners, professionals, and academicians of various scientific fields in exploring and better understanding these state-of-the-art technologies, their advancements, impact, future potentials and benefits, and their role in successfully achieving SDGs.The book:· Offers an in-depth overview of AIoT for achieving SDGs.· Presents the fusion of AI and IoT for bringing a significant change in everyday life and fulfilling SDGs.· Highlights innovative solutions and results of AIoT integration in several domains for achieving SDGs.· Showcases the influence of AIoT on promoting and improving sustainability in the context of SDGs.· Discusses the issues, benefits, solutions, and impact of AIoT in society, industry, and environment for achieving SDGs.
Artificial Intelligence on Dark Matter and Dark Energy: Reverse Engineering of the Big Bang (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Ariel FernándezAs we prod the cosmos at very large scales, basic tenets of physics seem to crumble under the weight of contradicting evidence. This book helps mitigate the crisis. It resorts to artificial intelligence (AI) for answers and describes the outcome of this quest in terms of an ur-universe, a quintessential compact multiply connected space that incorporates a fifth dimension to encode space-time as a latent manifold. In some ways, AI is bolder than humans because the huge corpus of knowledge, starting with the prodigious Standard Model (SM) of particle physics, poses almost no burden to its conjecture-framing processes. Why not feed AI with the SM enriched by the troubling cosmological phenomenology on dark matter and dark energy and see where AI takes us vis-à-vis reconciling the conflicting data with the laws of physics? This is precisely the intellectual adventure described in this book and – to the best of our knowledge – in no other book on the shelf. As the reader will discover, many AI conjectures and validations ultimately make a lot of sense, even if their boldness does not feel altogether "human" yet. This book is written for a broad readership. Prerequisites are minimal, but a background in college math/physics/computer science is desirable. This book does not merely describe what is known about dark matter and dark energy but also provides readers with intellectual tools to engage in a quest for the deepest cosmological mystery.
Artificial Intelligence on Medical Data: Proceedings of International Symposium, ISCMM 2021 (Lecture Notes in Computational Vision and Biomechanics #37)
by Mousumi Gupta Sujata Ghatak Amlan Gupta Abir Lal MukherjeeThis book includes high-quality papers presented at the Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021), organized by Computer Applications Department, SMIT in collaboration with Department of Pathology, SMIMS, Sikkim, India, and funded by Indian Council of Medical Research, during 11 – 12 November 2021. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.
The Artificial Intelligence Playbook: Time-Saving Tools for Teachers that Make Learning More Engaging
by Douglas Fisher Nancy Frey Meghan HargraveTime Saving AI Tools that Make Learning More Engaging Busy educators need tools that support their planning and provide them with more time with students. While Artificial Intelligence (AI) has emerged as a promising solution, it can only help if we’re willing to learn how to use it in ways that improve upon what we already do well. The Artificial Intelligence Playbook: Time Saving Tools that Make Learning More Engaging is here to empower teachers to explore AI’s potential and discover practical ways to implement it to enhance their planning and instruction. Two chapters and 6 "Educator Functions" guide teachers step-by-step through how to purposely use AI to: Compose Writing Prompts and Avoid Plagiarism Manage Content Foster Student Engagement Meet Students’ Instructional Needs Assess Student Learning Continue Lifelong Learning Though AI has the potential to reduce workload for educators, it will never replace teachers. Your connection with students is irreplaceable—and greatly impacts their learning. Consider AI a valuable tool that provides you with more time to build and sustain those vital relationships with students and that can assist them in learning at the very same time.
The Artificial Intelligence Playbook: Time-Saving Tools for Teachers that Make Learning More Engaging
by Douglas Fisher Nancy Frey Meghan HargraveTime Saving AI Tools that Make Learning More Engaging Busy educators need tools that support their planning and provide them with more time with students. While Artificial Intelligence (AI) has emerged as a promising solution, it can only help if we’re willing to learn how to use it in ways that improve upon what we already do well. The Artificial Intelligence Playbook: Time Saving Tools that Make Learning More Engaging is here to empower teachers to explore AI’s potential and discover practical ways to implement it to enhance their planning and instruction. Two chapters and 6 "Educator Functions" guide teachers step-by-step through how to purposely use AI to: Compose Writing Prompts and Avoid Plagiarism Manage Content Foster Student Engagement Meet Students’ Instructional Needs Assess Student Learning Continue Lifelong Learning Though AI has the potential to reduce workload for educators, it will never replace teachers. Your connection with students is irreplaceable—and greatly impacts their learning. Consider AI a valuable tool that provides you with more time to build and sustain those vital relationships with students and that can assist them in learning at the very same time.
Artificial Intelligence Revolution: How AI Will Change our Society, Economy, and Culture
by Robin LiThe co-founder of Baidu explains how AI will transform human livelihood, from our economy and financial systems down to our daily lives. Written by Baidu cofounder Robin Li and prefaced by award-winning sci-fi writer Cixin Liu (author of The Three-Body Problem), Artificial Intelligence Revolution introduces Baidu&’s teams of top scientists and management as pioneers of movement toward AI. The book covers many of the latest AI-related ideas and technological developments, such as: Computational abilityBig data resourcesSetting the basic standards of AI in research and developmentAn introduction to the &“super brain&”Intelligent manufacturingDeep learningL4 automated vehiclesSmart finance The book describes the emergence of a &“smart&” society powered by technology and reflects on the challenges humanity is about to face. Li covers the most pressing AI-related ideas and technological developments, including: Will artificial intelligence replace human workers, and in what sectors of the economy? How will it affect healthcare and finance? How will daily human life change? Robin Li&’s Artificial Intelligence Revolution addresses these questions and more from the perspective of a pioneer of AI development. It's a must-read for anyone concerned about the emergence of a &“smart&” society powered by technology and the challenges humanity is about to face.
Artificial Intelligence Security and Privacy: First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3–5, 2023, Proceedings, Part II (Lecture Notes in Computer Science #14510)
by Jaideep Vaidya Moncef Gabbouj Jin LiThis two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3–5, 2023.The 40 regular papers and 23 workshop papers presented in this two-volume set were carefully reviewed and selected from 115 submissions. Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications.
Artificial Intelligence Security and Privacy: First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3–5, 2023, Proceedings, Part I (Lecture Notes in Computer Science #14509)
by Jaideep Vaidya Moncef Gabbouj Jin LiThis two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3–5, 2023.The 40 regular papers and 23 workshop papers presented in this two-volume set were carefully reviewed and selected from 115 submissions.Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications.
Artificial Intelligence Technologies for Computational Biology
by Ranjeet Kumar Rout Saiyed Umer Sabha Sheikh Amrit Lal SangalThis text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing.It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems.The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology.This book:• Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis.• Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems.• Presents the application of evolutionary computations for fractal visualization of sequence data.• Explores the use of genetic algorithms for pair-wise and multiple sequence alignments.• Examines the roles of efficient computational techniques in biology.
Artificial Intelligence Technology in Healthcare: Security and Privacy Issues (Advances in Smart Healthcare Technologies)
by Neha Sharma Deepak Sinwar Durgesh SrivastavaArtificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple technologies (i.e., Internet of Things [IoT], Federated Computing, and AI) for managing and securing smart healthcare systems. Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing-based real-time health monitoring. Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches. Focuses on latest research on privacy, security, and threat detection on COVID-19 through IoT. Illustrates initiatives for research in smart computing for advanced healthcare management systems. This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.
Artificial Intimacy: Virtual Friends, Digital Lovers, and Algorithmic Matchmakers
by Rob BrooksWhat happens when the human brain, which evolved over eons, collides with twenty-first-century technology? Machines can now push psychological buttons, stimulating and sometimes exploiting the ways people make friends, gossip with neighbors, and grow intimate with lovers. Sex robots present the humanoid face of this technological revolution—yet although it is easy to gawk at their uncanniness, more familiar technologies based in artificial intelligence and virtual reality are insinuating themselves into human interactions. Digital lovers, virtual friends, and algorithmic matchmakers help us manage our feelings in a world of cognitive overload. Will these machines, fueled by masses of user data and powered by algorithms that learn all the time, transform the quality of human life?Artificial Intimacy offers an innovative perspective on the possibilities of the present and near future. The evolutionary biologist Rob Brooks explores the latest research on intimacy and desire to consider the interaction of new technologies and fundamental human behaviors. He details how existing artificial intelligences can already learn and exploit human social needs—and are getting better at what they do. Brooks combines an understanding of core human traits from evolutionary biology with analysis of how cultural, economic, and technological contexts shape the ways people express them. Beyond the technology, he asks what the implications of artificial intimacy will be for how we understand ourselves.
Artificial Life: The Quest for a New Creation
by Steven LevyBiologists, mathematicians, and computer scientists learn what computers can do when given the opportunity to "think".
Artificial Muscles: Applications of Advanced Polymeric Nanocomposites
by Mohsen ShahinpoorSmart materials are the way of the future in a variety of fields, from biomedical engineering and chemistry to nanoscience, nanotechnology, and robotics. Featuring an interdisciplinary approach to smart materials and structures, this second edition of Artificial Muscles: Applications of Advanced Polymeric Nanocomposites has been fully updated to thoroughly review the latest knowledge of ionic polymeric conductor nanocomposites (IPCNCs), including ionic polymeric metal nanocomposites (IPMNCs) as biomimetic distributed nanosensors, nanoactuators, nanotransducers, nanorobots, artificial muscles, and electrically controllable intelligent polymeric network structures. Authored by one of the founding fathers of the field, the book introduces fabrication and manufacturing methods of several electrically and chemically active ionic polymeric sensors, actuators, and artificial muscles, as well as a new class of electrically active polymeric nanocomposites and artificial muscles. It also describes a few apparatuses for modeling and testing various artificial muscles to show the viability of chemoactive and electroactive muscles. It presents the theories, modeling, and numerical simulations of ionic polymeric artificial muscles’ electrodynamics and chemodynamics and features current industrial and medical applications of IPMNCs. By covering the fabrication techniques of and novel developments in advanced polymeric nanocomposites, this second edition continues to provides an accessible yet solid foundation to the subject while stimulating further research. Key features: Fully up to date with the latest cutting-edge discoveries in the field Authored by a world expert in the subject area Explores the exciting and growing topic of smart materials in medicine Mohsen Shahinpoor is Professor of Mechanical Engineering at the University of Maine and a leading expert in artificial muscles.