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Recent Advances in NLP: The Case of Arabic Language (Studies in Computational Intelligence #874)

by Mohamed Abd Elaziz Mohammed A. A. Al-qaness Ahmed A. Ewees Abdelghani Dahou

In light of the rapid rise of new trends and applications in various natural language processing tasks, this book presents high-quality research in the field. Each chapter addresses a common challenge in a theoretical or applied aspect of intelligent natural language processing related to Arabic language. Many challenges encountered during the development of the solutions can be resolved by incorporating language technology and artificial intelligence.The topics covered include machine translation; speech recognition; morphological, syntactic, and semantic processing; information retrieval; text classification; text summarization; sentiment analysis; ontology construction; Arabizi translation; Arabic dialects; Arabic lemmatization; and building and evaluating linguistic resources.This book is a valuable reference for scientists, researchers, and students from academia and industry interested in computational linguistics and artificial intelligence, especially for Arabic linguistics and related areas.

Recent Advances on Memetic Algorithms and its Applications in Image Processing (Studies in Computational Intelligence #873)

by D. Jude Hemanth B. Vinoth Kumar G. R. Karpagam Manavalan

This book includes original research findings in the field of memetic algorithms for image processing applications. It gathers contributions on theory, case studies, and design methods pertaining to memetic algorithms for image processing applications ranging from defence, medical image processing, and surveillance, to computer vision, robotics, etc. The content presented here provides new directions for future research from both theoretical and practical viewpoints, and will spur further advances in the field.

Recent Advances on Soft Computing and Data Mining: Proceedings of the Fourth International Conference on Soft Computing and Data Mining (SCDM 2020), Melaka, Malaysia, January 22–⁠23, 2020 (Advances in Intelligent Systems and Computing #978)

by Jemal H. Abawajy Rozaida Ghazali Nazri Mohd Nawi Mustafa Mat Deris

This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.

Recent Developments of Soil Mechanics and Geotechnics in Theory and Practice (Lecture Notes in Applied and Computational Mechanics #91)

by Theodoros Triantafyllidis

This book provides essential insights into recent developments in fundamental geotechnical engineering research. Special emphasis is given to a new family of constitutive soil description methods, which take into account the recent loading history and the dilatancy effects. Particular attention is also paid to the numerical implementation of multi-phase material under dynamic loads, and to geotechnical installation processes. In turn, the book addresses implementation problems concerning large deformations in soils during piling operations or densification processes, and discusses the limitations of the respective methods. Numerical simulations of dynamic consolidation processes are presented in slope stability analysis under seismic excitation. Lastly, achieving the energy transition from conventional to renewable sources will call for geotechnical expertise. Consequently, the book explores and analyzes a selection of interesting problems involving the stability and serviceability of supporting structures, and provides new solutions approaches for practitioners and scientists in geotechnical engineering. The content reflects the outcomes of the Colloquium on Geotechnical Engineering 2019 (Geotechnik Kolloquium), held in Karlsruhe, Germany in September 2019.

Recent Metaheuristics Algorithms for Parameter Identification (Studies in Computational Intelligence #854)

by Erik Cuevas Jorge Gálvez Omar Avalos

This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems. It also bridges the gap between recent metaheuristic techniques and interesting identification system methods that benefit from the convenience of metaheuristic schemes by explaining basic ideas of the proposed applications in ways that can be understood by readers new to these fields. As such it is a valuable resource for energy practitioners who are not researchers in metaheuristics. In addition, it offers members of the metaheuristic community insights into how system identification and energy problems can be translated into optimization tasks.

Recent Trends and Advances in Artificial Intelligence and Internet of Things (Intelligent Systems Reference Library #172)

by Raghvendra Kumar Valentina E. Balas Rajshree Srivastava

This book covers all the emerging trends in artificial intelligence (AI) and the Internet of Things (IoT). The Internet of Things is a term that has been introduced in recent years to define devices that are able to connect and transfer data to other devices via the Internet. While IoT and sensors have the ability to harness large volumes of data, AI can learn patterns in the data and quickly extract insights in order to automate tasks for a variety of business benefits. Machine learning, an AI technology, brings the ability to automatically identify patterns and detect anomalies in the data that smart sensors and devices generate, and it can have significant advantages over traditional business intelligence tools for analyzing IoT data, including being able to make operational predictions up to 20 times earlier and with greater accuracy than threshold-based monitoring systems. Further, other AI technologies, such as speech recognition and computer vision can help extract insights from data that used to require human review. The powerful combination of AI and IoT technology is helping to avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management.

Recent Trends in Communication and Intelligent Systems: Proceedings of ICRTCIS 2019 (Algorithms for Intelligent Systems)

by Neha Yadav Ajay Sharma Swagatam Das Harish Sharma Aditya Kumar Singh Pundir

The book gathers the best research papers presented at the International Conference on Recent Trends in Communication and Intelligent Systems (ICRTCIS 2019), organized by Rajasthan Technical University Kota, and Arya College of Engineering and IT, Jaipur, on 8–9 June 2019. It discusses the latest technologies in communication and intelligent systems, covering various areas of communication engineering, such as signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general. Featuring work by leading researchers and technocrats, the book serves as a valuable reference resource for young researchers and academics as well as practitioners in industry.

Recent Trends in Decision Science and Management: Proceedings of ICDSM 2019 (Advances in Intelligent Systems and Computing #1142)

by Vipul Jain Madjid Tavana Andrew W. H. Ip Tao-Sheng Wang

This book discusses an emerging field of decision science that focuses on business processes and systems used to extract knowledge from large volumes of data to provide significant insights for crucial decisions in critical situations. It presents studies employing computing techniques like machine learning, which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets, leadership, and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the 2nd International Conference on Decision Science and Management (ICDSM 2019), held at Hunan International Economics University, China, on 20–21 September 2019.

Recent Trends in Image and Signal Processing in Computer Vision (Advances in Intelligent Systems and Computing #1124)

by Sudip Paul Shruti Jain

This book highlights recent advances and emerging technologies that utilize computational intelligence in signal processing, computing, imaging science, artificial intelligence, and their applications. It covers all branches of artificial intelligence and machine learning that are based on computation at some level, e.g. artificial neural networks, evolutionary algorithms, fuzzy systems, and automatic medical identification systems. Exploring recent trends in research and applications, the book offers a valuable resource for professors, researchers, and engineers alike.

Recent Trends in Intelligent Computing, Communication and Devices: Proceedings of ICCD 2018 (Advances in Intelligent Systems and Computing #1006)

by Vipul Jain Ishwar K. Sethi Srikanta Patnaik Florin Popențiu Vlădicescu

This book gathers a collection of high-quality, peer-reviewed research papers presented at the International Conference on Intelligent Computing, Communication and Devices (ICCD 2018), which address three core dimensions of the intelligent sciences—intelligent computing, intelligent communication, and intelligent devices. Intelligent computing includes areas such as intelligent and distributed computing, intelligent grid and cloud computing, Internet of Things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. In turn, intelligent communication is concerned with communication and network technologies, such as mobile broadband and all-optical networks, which are the key to groundbreaking advances in intelligent communication technologies. It includes communication hardware, software and networked intelligence, mobile technologies, machine-to-machine communication networks, speech and natural language processing, routing techniques and network analytics, wireless ad hoc and sensor networks, communications and information security, signal, image and video processing, network management, and traffic engineering. Lastly, intelligent devices refer to any equipment, instruments, or machines that have their own computing capability, and covers areas such as embedded systems, radiofrequency identification (RFID), radiofrequency microelectromechanical systems (RF MEMS), very large-scale integration (VLSI) design and electronic devices, analog and mixed-signal integrated circuit (IC) design and testing, microelectromechanical systems (MEMS) and microsystems, solar cells and photonics, nanodevices, single electron and spintronic devices, space electronics, and intelligent robotics.

Recent Trends in Learning From Data: Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019) (Studies in Computational Intelligence #896)

by Luca Oneto Davide Anguita Nicolò Navarin Alessandro Sperduti

This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Recent Trends in Mechanical Engineering: Select Proceedings of ICIME 2019 (Lecture Notes in Mechanical Engineering)

by G. S. V. L. Narasimham A. Veeresh Babu S. Sreenatha Reddy Rajagopal Dhanasekaran

This book comprises select peer-reviewed proceedings from the International Conference on Innovations in Mechanical Engineering (ICIME 2019). The volume covers current research in almost all major areas of mechanical engineering, and is divided into six parts: (i) automobile and thermal engineering, (ii) design and optimization, (iii) production and industrial engineering, (iv) material science and metallurgy, (v) nanoscience and nanotechnology, and (vi) renewable energy sources and CAD/CAM/CFD. The topics provide insights into different aspects of designing, modeling, manufacturing, optimizing, and processing with wide ranging applications. The contents of this book can be of interest to researchers and professionals alike.

Reclaiming Personalized Learning: A Pedagogy for Restoring Equity and Humanity in Our Classrooms

by Paul Emerich France

Where exactly did personalized learning go so wrong? For teacher and consultant Paul France, at first technology-powered personalized learning seemed like a panacea. But after three years spent at a personalized learning start-up and network of microschools, he soon realized that such corporate-driven individualized learning initiatives do more harm than good, especially among our most vulnerable students. The far-superior alternative? A human-centered pedagogy that prioritizes children over technology. First, let’s be clear: Reclaiming Personalized Learning is not yet-another ed tech book. Instead it’s a user’s guide to restoring equity and humanity to our classrooms and schools through personalization. One part polemical, eleven parts practical, the book describes how to: Shape whole-class instruction, leverage small-group interactions, and nurture a student’s inner-dialogue Cultivate awareness within and among students, and build autonomy and authority Design curriculum with a flexible frame and where exactly the standards fit Humanize assessment and instruction, including the place of responsive teaching Create a sense of belonging, humanize technology integration, and effect socially just teaching and learning—all central issues in equity The truth is this: there’s no one framework, there’s no one tool that makes learning personalized–what personalized learning companies with a vested interest in profits might tempt you to believe. It’s people who personalize learning, and people not technology must be at the center of education. The time is now for all of us teachers to reclaim personalized learning, and this all-important book is our very best resource for getting started. “This is a compelling and critically important book for our time. With rich stories of teaching and learning Paul France considers ways to create the most positive learning experiences possible.” - JO BOALER, Nomellini & Olivier Professor of Education, Stanford Graduate School of Education “This brilliant book is a major contribution to the re-imagination of learning and teaching for the twenty-first century and should be essential reading for new and experienced teachers alike." - TONY WAGNER, Senior Research Fellow, Learning Policy Institute “In these troubled times, this book is more than a breath of fresh air, it is a call to action. Paul gives us an accessible and sophisticated book that explains how and why we should celebrate the humanity of every single student.” - JIM KNIGHT, Senior Partner of the Instructional Coaching Group (ICG) and Author of The Impact Cycle

Reclaiming Personalized Learning: A Pedagogy for Restoring Equity and Humanity in Our Classrooms

by Paul Emerich France

Where exactly did personalized learning go so wrong? For teacher and consultant Paul France, at first technology-powered personalized learning seemed like a panacea. But after three years spent at a personalized learning start-up and network of microschools, he soon realized that such corporate-driven individualized learning initiatives do more harm than good, especially among our most vulnerable students. The far-superior alternative? A human-centered pedagogy that prioritizes children over technology. First, let’s be clear: Reclaiming Personalized Learning is not yet-another ed tech book. Instead it’s a user’s guide to restoring equity and humanity to our classrooms and schools through personalization. One part polemical, eleven parts practical, the book describes how to: Shape whole-class instruction, leverage small-group interactions, and nurture a student’s inner-dialogue Cultivate awareness within and among students, and build autonomy and authority Design curriculum with a flexible frame and where exactly the standards fit Humanize assessment and instruction, including the place of responsive teaching Create a sense of belonging, humanize technology integration, and effect socially just teaching and learning—all central issues in equity The truth is this: there’s no one framework, there’s no one tool that makes learning personalized–what personalized learning companies with a vested interest in profits might tempt you to believe. It’s people who personalize learning, and people not technology must be at the center of education. The time is now for all of us teachers to reclaim personalized learning, and this all-important book is our very best resource for getting started. “This is a compelling and critically important book for our time. With rich stories of teaching and learning Paul France considers ways to create the most positive learning experiences possible.” - JO BOALER, Nomellini & Olivier Professor of Education, Stanford Graduate School of Education “This brilliant book is a major contribution to the re-imagination of learning and teaching for the twenty-first century and should be essential reading for new and experienced teachers alike." - TONY WAGNER, Senior Research Fellow, Learning Policy Institute “In these troubled times, this book is more than a breath of fresh air, it is a call to action. Paul gives us an accessible and sophisticated book that explains how and why we should celebrate the humanity of every single student.” - JIM KNIGHT, Senior Partner of the Instructional Coaching Group (ICG) and Author of The Impact Cycle

Recommender System with Machine Learning and Artificial Intelligence: Practical Tools and Applications in Medical, Agricultural and Other Industries

by Jyotir Moy Chatterjee Sachi Nandan Mohanty Sarika Jain Priya Gupta Ahmed A. Elngar

This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. It comprehensively covers the topic of recommender systems, which provide personalized recommendations of items or services to the new users based on their past behavior. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations in agricultural or healthcare domains and contexts, the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. This book illustrates how this technology can support the user in decision-making, planning and purchasing processes in agricultural & healthcare sectors.

Reconfigurable Cellular Neural Networks and Their Applications (SpringerBriefs in Applied Sciences and Technology)

by Müştak E. Yalçın Tuba Ayhan Ramazan Yeniçeri

This book explores how neural networks can be designed to analyze sensory data in a way that mimics natural systems. It introduces readers to the cellular neural network (CNN) and formulates it to match the behavior of the Wilson–Cowan model. In turn, two properties that are vital in nature are added to the CNN to help it more accurately deliver mimetic behavior: randomness of connection, and the presence of different dynamics (excitatory and inhibitory) within the same network. It uses an ID matrix to determine the location of excitatory and inhibitory neurons, and to reconfigure the network to optimize its topology. The book demonstrates that reconfiguring a single-layer CNN is an easier and more flexible solution than the procedure required in a multilayer CNN, in which excitatory and inhibitory neurons are separate, and that the key CNN criteria of a spatially invariant template and local coupling are fulfilled. In closing, the application of the authors’ neuron population model as a feature extractor is exemplified using odor and electroencephalogram classification.

Redesigning Organizations: Concepts for the Connected Society

by Denise Feldner

This book offers readers a deeper understanding of the Cyberspace, of how institutions and industries are reinventing themselves, helping them excel in the transition to a fully digitally connected global economy. Though technology plays a key part in this regard, societal acceptance is the most important underlying condition, as it poses pressing challenges that cut across companies, developers, governments and workers. The book explores the challenges and opportunities involved, current and potential future concepts, critical reflections and best practices. It addresses connected societies, new opportunities for governments, the role of trust in digital networks, and future education networks. In turn, a number of representative case studies demonstrate the current state of development in practice.

Rediscovering Heritage Through Technology: A Collection of Innovative Research Case Studies That Are Reworking The Way We Experience Heritage (Studies in Computational Intelligence #859)

by Dylan Seychell Alexiei Dingli

With the proliferation of technology, science became a medium used to create and interpret heritage in a way that redefines human achievements. The recent advances in technology are providing us with a variety of tools aimed at exploring, experiencing and interacting with heritage in a completely new way, which was unimaginable up until a few decades ago. Suddenly, heritage has become accessible and exciting to those who might not have previously considered it interesting. This book presents a selection of approaches in various topics such as artificial intelligence, gamification, and virtual and augmented reality, and uses practical examples to show how they can be deployed in real-world scenarios. As such, it inspires a wide variety of stakeholders and helps them experience our common heritage through a new lens.

Refactoring Legacy T-SQL for Improved Performance: Modern Practices for SQL Server Applications

by Lisa Bohm

Breathe new life into older applications by refactoring T-SQL queries and code using modern techniques. This book shows you how to significantly improve the performance of older applications by finding common anti-patterns in T-SQL code, then rewriting those anti-patterns using new functionality that is supported in current versions of SQL Server, including SQL Server 2019. The focus moves through the different types of database objects and the code used to create them, discussing the limitations and anti-patterns commonly found for each object type in your database.Legacy code isn’t just found in queries and external applications. It’s also found in the definitions of underlying database objects such as views and tables. This book helps you quickly find problematic code throughout the database and points out where and how modern solutions can replace older code, thereby making your legacy applications run faster and extending their lifetimes. Author Lisa Bohm explains the logic behind each anti-pattern, helping you understand why each pattern is a problem and showing how it can be avoided. Good coding habits are discussed, including guidance on topics such as readability and maintainability. What You Will LearnFind specific areas in code to target for performance gainsIdentify pain points quickly and understand why they are problematicRewrite legacy T-SQL to reduce or eliminate hidden performance issuesWrite modern code with an awareness of readability and maintainabilityRecognize and correlate T-SQL anti-patterns with techniques for better solutionsMake a positive impact on application user experience in your organizationWho This Book Is ForDatabase administrators or developers who maintain older code, those frustrated with complaints about slow code when there is so much of it to fix, and those who want a head start in making a positive impact on application user experience in their organization

Regulating Artificial Intelligence

by Thomas Wischmeyer Timo Rademacher

This book assesses the normative and practical challenges for artificial intelligence (AI) regulation, offers comprehensive information on the laws that currently shape or restrict the design or use of AI, and develops policy recommendations for those areas in which regulation is most urgently needed. By gathering contributions from scholars who are experts in their respective fields of legal research, it demonstrates that AI regulation is not a specialized sub-discipline, but affects the entire legal system and thus concerns all lawyers. Machine learning-based technology, which lies at the heart of what is commonly referred to as AI, is increasingly being employed to make policy and business decisions with broad social impacts, and therefore runs the risk of causing wide-scale damage. At the same time, AI technology is becoming more and more complex and difficult to understand, making it harder to determine whether or not it is being used in accordance with the law. In light of this situation, even tech enthusiasts are calling for stricter regulation of AI. Legislators, too, are stepping in and have begun to pass AI laws, including the prohibition of automated decision-making systems in Article 22 of the General Data Protection Regulation, the New York City AI transparency bill, and the 2017 amendments to the German Cartel Act and German Administrative Procedure Act. While the belief that something needs to be done is widely shared, there is far less clarity about what exactly can or should be done, or what effective regulation might look like. The book is divided into two major parts, the first of which focuses on features common to most AI systems, and explores how they relate to the legal framework for data-driven technologies, which already exists in the form of (national and supra-national) constitutional law, EU data protection and competition law, and anti-discrimination law. In the second part, the book examines in detail a number of relevant sectors in which AI is increasingly shaping decision-making processes, ranging from the notorious social media and the legal, financial and healthcare industries, to fields like law enforcement and tax law, in which we can observe how regulation by AI is becoming a reality.

Regulating FinTech in Asia: Global Context, Local Perspectives (Perspectives in Law, Business and Innovation)

by Steven Van Uytsel Mark Fenwick Bi Ying

This book focuses on Fintech regulation in Asian, situating local developments in broader economic, regulatory and technological contexts. Over the last decade, Fintech – broadly defined as the use of new information technologies to help financial institutions and intermediaries compete in the marketplace – has disrupted the financial services sector. Like other 21st century technological developments, Fintech is a global phenomenon that plays out in local economic, political and regulatory contexts, and this dynamic interplay between global trends and local circumstances has created a complex and fast-changing landscape. Diverse stakeholders (most obviously incumbent financial service providers, tech start-ups and regulators) all pursue a competitive edge against a background of profound uncertainty about the future direction and possible effects of multiple emerging technologies. Compounding these difficulties are uncertainties surrounding regulatory responses. Policymakers often struggle to identify appropriate regulatory responses and increasingly turn to policy experimentation. Such issues add to the challenges for the various actors operating in the Fintech space. This situation is particularly fluid in Asia, since many jurisdictions are seeking to establish themselves as a regional hub for new financial services.

Reimagining Philosophy and Technology, Reinventing Ihde (Philosophy of Engineering and Technology #33)

by Ashley Shew Glen Miller

This volume includes eleven original essays that explore and expand on the work of Don Ihde, bookended by two chapters by Ihde himself. Ihde, the recipient of the first Society for Philosophy and Technology's Lifetime Achievement Award in 2017, is best known for his development of postphenomenology, a blend of pragmatism and phenomenology that incorporates insights into the ways technology mediates human perception and action.The book contains contributions from academics from Europe, North America, and Asia, which demonstrates the global impact of Ihde’s work. Essays in the book explore the relationship between Ihde's work and its origins in phenomenology (especially Husserl and Heidegger) and American pragmatism; integrate his philosophical work within the embodied experience of radical architecture and imagine the possibility of a future philosophy of technology after postphenomenology;develop central ideas of postphenomenology and expand the resources present in postphenomenology to ethics and politics; andextend the influence of Ihde's ideas to mobile media and engineering, and comprehensively assess the influence of his work in China. The book includes a reprint of the Introduction of Sense and Significance, one of Ihde's first books; "Hawk: Predatory Vision," a new chapter that blends his biographical experience with feminism, technoscience, and environmental observation; and an appendix that lists all of Ihde's books as well as secondary sources annotated by Ihde himself. Starting with an Editors' Introduction that offers an overview of the central ideas in Ihde's corpus and concluding with an index that facilitates research across the various chapters, this book is of interest to a diverse academic community that includes philosophers, STM scholars, anthropologists, historians, and sociologists.

Reinforcement Learning of Bimanual Robot Skills (Springer Tracts in Advanced Robotics #134)

by Adrià Colomé Carme Torras

This book tackles all the stages and mechanisms involved in the learning of manipulation tasks by bimanual robots in unstructured settings, as it can be the task of folding clothes. The first part describes how to build an integrated system, capable of properly handling the kinematics and dynamics of the robot along the learning process. It proposes practical enhancements to closed-loop inverse kinematics for redundant robots, a procedure to position the two arms to maximize workspace manipulability, and a dynamic model together with a disturbance observer to achieve compliant control and safe robot behavior. In the second part, methods for robot motion learning based on movement primitives and direct policy search algorithms are presented. To improve sampling efficiency and accelerate learning without deteriorating solution quality, techniques for dimensionality reduction, for exploiting low-performing samples, and for contextualization and adaptability to changing situations are proposed. In sum, the reader will find in this comprehensive exposition the relevant knowledge in different areas required to build a complete framework for model-free, compliant, coordinated robot motion learning.

Reinventing Clinical Decision Support: Data Analytics, Artificial Intelligence, and Diagnostic Reasoning

by Paul Cerrato John Halamka

This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it’s forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

Relational and Algebraic Methods in Computer Science: 18th International Conference, RAMiCS 2020, Palaiseau, France, April 8–11, 2020, Proceedings (Lecture Notes in Computer Science #12062)

by Michael Winter Peter Jipsen Uli Fahrenberg

This book constitutes the proceedings of the 18th International Conference on Relational and Algebraic Methods in Computer Science, RAMiCS 2020, which was due to be held in Palaiseau, France, in April 2020. The conference was cancelled due to the COVID-19 pandemic. The 20 full papers presented together with 3 invited abstracts were carefully selected from 29 submissions. Topics covered range from mathematical foundations to applications as conceptual and methodological tools in computer science and beyond.

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