Browse Results

Select your format based upon: 1) how you want to read your book, and 2) compatibility with your reading tool. To learn more about using Bookshare with your device, visit the Help Center.

Here is an overview of the specialized formats that Bookshare offers its members with links that go to the Help Center for more information.

• Bookshare Web Reader - A customized reading tool for Bookshare members offering all the features of DAISY with a single click of the "Read Now" link.
• DAISY (Digital Accessible Information System) - A digital book file format. DAISY books from Bookshare are DAISY 3.0 text files that work with just about every type of access technology that reads text. Books that contain images will have the download option of ‘DAISY Text with Images’.
• BRF (Braille Refreshable Format) - Digital Braille for use with refreshable Braille devices and Braille embossers.
• MP3 (MPEG audio layer 3) - Provides audio only with no text. These books are created with a text-to-speech engine and spoken by Kendra, a high quality synthetic voice from Ivona. Any device that supports MP3 playback is compatible.
• DAISY Audio - Similar to the DAISY option above; however, this option uses MP3 files created with our text-to-speech engine that utilizes Ivonas Kendra voice. This format will work with Daisy Audio compatible players such as Victor Reader Stream and Read2Go.
• EPUB - A standard e-book format that can be read on many tools, such as iBooks, Readium or others.
• Word - Accessible Word output, which can be unzipped and opened in any tool that allows .docx files

Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium: 23rd International Conference, AIED 2022, Durham, UK, July 27–31, 2022, Proceedings, Part II (Lecture Notes in Computer Science #13356)

This two-volume set LNAI 13355 and 13356 constitutes the refereed proceedings of the 23rd International Conference on Artificial Intelligence in Education, AIED 2022, held in Durham, UK, in July 2022.The 40 full papers and 40 short papers presented together with 2 keynotes, 6 industry papers, 12 DC papers, 6 Workshop papers, 10 Practitioner papers, 97 Posters and Late-Breaking Results were carefully reviewed and selected from 243 submissions. The conference presents topics such as intelligent systems and the cognitive sciences for the improvement and advancement of education, the science and engineering of intelligent interactive learning systems. The theme for the AIED 2022 conference was „AI in Education: Bridging the gap between academia, business, and non-pro t in preparing future-proof generations towards ubiquitous AI."

Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky: 25th International Conference, AIED 2024, Recife, Brazil, July 8–12, 2024, Proceedings, Part II (Communications in Computer and Information Science #2151)

This volume constitutes poster papers and late breaking results presented during the 25th International Conference on Artificial Intelligence in Education, AIED 2024, which took place in Recife, Brazil, during July 8–12, 2024. The 18 full papers and 92 short papers were carefully reviewed and selected from 200 submissions. They are organized in topical sections as follows: Part One: Blue Sky, Industry, Innovation and Practitioner, WideAIED and Late-Breaking Results. Part Two: Late-Breaking Results, Doctoral Consortium, Workshops and Tutorials.

Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky: 25th International Conference, AIED 2024, Recife, Brazil, July 8–12, 2024, Proceedings, Part I (Communications in Computer and Information Science #2150)

This volume constitutes poster papers and late breaking results presented during the 25th International Conference on Artificial Intelligence in Education, AIED 2024, which took place in Recife, Brazil, during July 8–12, 2024. The 18 full papers and 92 short papers were carefully reviewed and selected from 200 submissions. They are organized in topical sections as follows: Part One: Blue Sky, Industry, Innovation and Practitioner, WideAIED and Late-Breaking Results. Part Two: Late-Breaking Results, Doctoral Consortium, Workshops and Tutorials.

Artificial Intelligence in Education: The Power and Dangers of ChatGPT in the Classroom (Studies in Big Data #144)

This book aims to bring together a collection of innovative and cutting-edge research that addresses the various challenges in the application and theoretical aspects of ChatGPT in education. ChatGPT is a large language model developed by OpenAI that has the ability to generate human-like text based on a prompt. This has significant potential for use in the field of education, as it allows for the creation of personalized, interactive learning experiences, automating assessment and grading, and more. In e-learning, ChatGPT is used to provide instant feedback and support to students, as well as generate interactive conversations in the target language for language learning. It is also integrated with existing learning management systems and educational technology platforms to enhance their capabilities. In research, ChatGPT is used for natural language processing and sentiment analysis to gather insights on student learning experiences and educational outcomes. However, it is important to note that there are also ethical and privacy concerns that come with using language models like ChatGPT in education, such as data protection and the potential for bias. Overall, the use of ChatGPT in education has the potential to revolutionize the way we learn, teach, and access information. The book seeks to publish original manuscripts that cover a broad range of topics, from the development of new chatbot technologies and their integration into the classroom, to the examination of the ethical and pedagogical implications of these systems. By compiling the latest developments in the field and highlighting new areas for exploration, this book provides valuable insights and perspectives for researchers, educators, and practitioners working in the field of ChatGPT and education. The ultimate goal is to advance the understanding of ChatGPT and its role in education and to promote its effective and responsible use in the classroom and beyond.

Artificial Intelligence in Financial Markets: Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics (New Developments in Quantitative Trading and Investment)

As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.

Artificial Intelligence in HCI: Second International Conference, AI-HCI 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings (Lecture Notes in Computer Science #12797)

This book constitutes the refereed proceedings of the Second International Conference on Artificial Intelligence in HCI, AI-HCI 2021, which was held as part of HCI International 2021 and took place virtually during July 24-29, 2021.The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. The papers included in this volume were organized in topical sections as follows: Ethics, trust and explainability; human-centered AI; AI applications in HCI; and AI applications in smart environments.

Artificial Intelligence in Healthcare

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data miningIllustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networksIncludes applications and case studies across all areas of AI in healthcare data

Artificial Intelligence in Healthcare: First International Conference, AIiH 2024, Swansea, UK, September 4–6, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14975)

The two-volume set LNCS 14975 + 14976 constitutes the proceedings of the First International Conference on Artificial Intelligence in Healthcare, AIiH 2024, which took place in Swansea, UK, in September 2024. The 47 full papers included in the proceedings were carefully reviewed and selected from 70 submissions. They were organized in the following topical sections: Part I: Personalised Healthcare and Medicine; AI driven early diagnosis and prevention; AI driven robotics for healthcare; AI in mental health; Part II: AI in proactive care and intervention; AI-aided medical imaging and analysis; Medical signal and image processing; Assisted living technology; Digital twinning, virtual pathology and oncology; Patient data, privacy and ethics.

Artificial Intelligence in Healthcare and Medicine

This 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 Healthcare and Medicine

This 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 Industrial Decision Making, Control and Automation (Intelligent Systems, Control and Automation: Science and Engineering #14)

This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems.

Artificial Intelligence in Logic Design (The Springer International Series in Engineering and Computer Science #766)

There are three outstanding points of this book. First: for the first time, a collective point of view on the role of artificial intelligence paradigm in logic design is introduced. Second, the book reveals new horizons of logic design tools on the technologies of the near future. Finally, the contributors of the book are twenty recognizable leaders in the field from the seven research centres. The chapters of the book have been carefully reviewed by equally qualified experts. All contributors are experienced in practical electronic design and in teaching engineering courses. Thus, the book's style is accessible to graduate students, practical engineers and researchers.

Artificial Intelligence in Manufacturing: Enabling Intelligent, Flexible and Cost-Effective Production Through AI

This open access book presents a rich set of innovative solutions for artificial intelligence (AI) in manufacturing. The various chapters of the book provide a broad coverage of AI systems for state of the art flexible production lines including both cyber-physical production systems (Industry 4.0) and emerging trustworthy and human-centered manufacturing systems (Industry 5.0). From a technology perspective, the book addresses a wide range of AI paradigms such as deep learning, reinforcement learning, active learning, agent-based systems, explainable AI, industrial robots, and AI-based digital twins. Emphasis is put on system architectures and technologies that foster human-AI collaboration based on trusted interactions between workers and AI systems. From a manufacturing applications perspective, the book illustrates the deployment of these AI paradigms in a variety of use cases spanning production planning, quality control, anomaly detection, metrology, workers’ training, supply chain management, as well as various production optimization scenarios. This is an open access book.

Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings (Lecture Notes in Computer Science #10259)

This book constitutes the refereed proceedings of the 16th Conference on Artificial Intelligence in Medicine, AIME 2017, held in Vienna, Austria, in June 2017.The 21 revised full and 23 short papers presented were carefully reviewed and selected from 113 submissions. The papers are organized in the following topical sections: ontologies and knowledge representation; Bayesian methods; temporal methods; natural language processing; health care processes; and machine learning, and a section with demo papers.

Artificial Intelligence in Medicine: Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, Aalborg, Denmark, June 20-24, 1999, Proceedings (Lecture Notes in Computer Science #1620)

Artificial Intelligence in Medicine: 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12–15, 2023, Proceedings (Lecture Notes in Computer Science #13897)

This book constitutes the refereed proceedings of the 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, held in Portoroz, Slovenia, in June12–15, 2023.The 23 full papers and 21 short papers presented together with 3 demonstration papers were selected from 108 submissions. The papers are grouped in topical sections on: machine learning and deep learning; explainability and transfer learning; natural language processing; image analysis and signal analysis; data analysis and statistical models; knowledge representation and decision support.

Artificial Intelligence in Medicine: 18th International Conference on Artificial Intelligence in Medicine, AIME 2020, Minneapolis, MN, USA, August 25–28, 2020, Proceedings (Lecture Notes in Computer Science #12299)

The LNAI 12299 constitutes the papers of the 18th International Conference on Artificial Intelligence in Medicine, AIME 2020, which will be held online in August 2020. The 42 full papers presented together with 1short papers in this volume were carefully reviewed and selected from a total of 103 submissions. The AIME 2020 goals were to present and consolidate the international state of the art of AI in biomedical research from the perspectives of theory, methodology, systems, and applications.

Artificial Intelligence in Medicine: 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14844)

This two-volume set LNAI 14844-14845 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Medicine, AIME 2024, held in Salt Lake City, UT, USA, during July 9-12, 2024. The 54 full papers and 22 short papers presented in the book were carefully reviewed and selected from 335 submissions. The papers are grouped in the following topical sections: Part I: Predictive modelling and disease risk prediction; natural language processing; bioinformatics and omics; and wearable devices, sensors, and robotics. Part II: Medical imaging analysis; data integration and multimodal analysis; and explainable AI.

Artificial Intelligence in Medicine: 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part II (Lecture Notes in Computer Science #14845)

This two-volume set LNAI 14844-14845 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Medicine, AIME 2024, held in Salt Lake City, UT, USA, during July 9-12, 2024. The 54 full papers and 22 short papers presented in the book were carefully reviewed and selected from 335 submissions. The papers are grouped in the following topical sections: Part I: Predictive modelling and disease risk prediction; natural language processing; bioinformatics and omics; and wearable devices, sensors, and robotics. Part II: Medical imaging analysis; data integration and multimodal analysis; and explainable AI.

Artificial Intelligence in Medicine: 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings (Lecture Notes in Computer Science #11526)

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Artificial Intelligence in Medicine: 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, Virtual Event, June 15–18, 2021, Proceedings (Lecture Notes in Computer Science #12721)

This book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, held as a virtual event, in June 2021. The 28 full papers presented together with 30 short papers were selected from 138 submissions. The papers are grouped in topical sections on image analysis; predictive modelling; temporal data analysis; unsupervised learning; planning and decision support; deep learning; natural language processing; and knowledge representation and rule mining.

Artificial Intelligence in Music, Sound, Art and Design: 13th International Conference, EvoMUSART 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings (Lecture Notes in Computer Science #14633)

This book constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2024, held as part of EvoStar 2024, in Aberystwyth, UK, April 3–5, 2024. The 17 full papers and 8 short papers presented in this book were carefully reviewed and selected from 55 submissions. The main purpose of this conference proceedings was to bring together practitioners who are using Artificial Intelligence techniques for artistic tasks, providing the opportunity to promote, present, and discuss ongoing work in the area.

Artificial Intelligence in Music, Sound, Art and Design: 12th International Conference, EvoMUSART 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (Lecture Notes in Computer Science #13988)

This book constitutes the refereed proceedings of the 12th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2023, held as part of Evo* 2023, in April 2023, co-located with the Evo* 2023 events, EvoCOP, EvoApplications, and EuroGP.The 20 full papers and 7 short papers presented in this book were carefully reviewed and selected from 55 submissions. They cover a wide range of topics and application areas of artificial intelligence, including generative approaches to music and visual art, deep learning, and architecture.

Artificial Intelligence in Music, Sound, Art and Design: 10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings (Lecture Notes in Computer Science #12693)

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, held as part of Evo* 2021, as Virtual Event, in April 2021, co-located with the Evo* 2021 events, EvoCOP, EvoApplications, and EuroGP. The 24 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

Artificial Intelligence in Prescriptive Analytics: Innovations in Decision Analysis, Intelligent Optimization, and Data-Driven Decisions (Intelligent Systems Reference Library #260)

Considering the advances of the different approaches and applications in the last years, and even in the last months, this is a particular moment in history to transform every data-driven decision-making process with the power of Artificial Intelligence (AI). This book reveals, through concrete case studies and original application ideas, how cutting-edge AI techniques are revolutionizing industries such as finance, health care, and manufacturing. It invites us to discover how machine learning, decision analysis, and intelligent optimization are changing, directly or indirectly, almost all aspects of our daily lives. This comprehensive book offers practical insights and real-world applications for professionals, researchers, and students alike. It helps to learn how to apply AI for smarter, data-driven decisions in areas like supply chain management, risk assessment, and even personalized medicine. Be inspired by the chapters of this book and unlock the full potential of AI in your field!