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Artificial Intelligence in Mechanical and Industrial Engineering (Artificial Intelligence (AI) in Engineering)
by J. Paulo Davim Kaushik Kumar Divya ZindaniArtificial Intelligence in Mechanical and Industrial Engineering offers a unified platform for the dissemination of basic and applied knowledge on the integration of artificial intelligence within the realm of mechanical and industrial engineering. The book covers the tools and information needed to build successful careers and a source of knowledge for those working with AI within these domains. The book offers a systematic approach to explicate fundamentals as well as recent advances. It incorporates various case studies for major topics as well as numerous examples. It will also include real-time intelligent automation and associated supporting methodologies and techniques, and cover decision-support systems, as well as applications of Chaos Theory and Fractals. The book will give scientists, researchers, instructors, students, and practitioners the tools and information needed to build successful careers and to be an impetus to advancements in next-generation mechanical and industrial engineering domains.
Artificial Intelligence in Mechatronics and Civil Engineering: Bridging the Gap (Emerging Trends in Mechatronics)
by Aydin Azizi Danial Jahed Armaghani Ehsan MomeniRecent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering is highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book.
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 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 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 Medicine and Healthcare
by Ajay Kumar Mamta Dahiya Sangeeta Rani Sarita Rathee Naveen HemrajaniThis book is discussing artificial intelligence-based smart systems for diagnosis and prediction of diseases, artificial intelligence in clinical decision-making, and artificial intelligence tools for clinical and healthcare data. It further highlights the importance of 5G and 6G communication for telemedicine applications and applications of machine learning and deep learning in pandemic epidemiology.This book: Discusses artificial intelligence-inspired Internet of Things-based solutions, and machine learning modeling for smart healthcare Explains the use of computer vision, natural language processing in healthcare, and artificial intelligence in clinical decision-making Illustrates the role of artificial intelligence in telemedicine applications Examines medical image analysis using machine learning, and deep learning techniques It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields including computer science and engineering, electronics and communications engineering, and biomedical engineering.
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)
by Martin Michalowski Robert MoskovitchThe 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: 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Portorož, Slovenia, June 12–15, 2023, Proceedings (Lecture Notes in Computer Science #13897)
by Allan Tucker Mar Marcos Jose M. Juarez Gregor StiglicThis 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: 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14844)
by Robert Moskovitch Joseph Finkelstein Enea ParimbelliThis 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)
by Robert Moskovitch Joseph Finkelstein Enea ParimbelliThis 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: AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26–29, 2019, Revised Selected Papers (Lecture Notes in Computer Science #11979)
by Richard Lenz Mor Peleg Jerzy Stefanowski Grzegorz J. Nalepa Mar Marcos Jose M. Juarez Slawomir Nowaczyk Gregor StiglicThis book constitutes revised selected papers from the AIME 2019 workshops KR4HC/ProHealth 2019, the Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care, and TEAAM 2019, the Workshop on Transparent, Explainable and Affective AI in Medical Systems. The volume contains 5 full papers from KR4HC/ProHealth, which were selected out of 13 submissions. For TEAAM 8 papers out of 10 submissions were accepted for publication.
Artificial Intelligence in Medicine: Applications, Limitations and Future Directions
by Erwin Loh Manda Raz Tam C. NguyenThis 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 Models, Methods and Applications (Studies in Systems, Decision and Control #457)
by Vladik Kreinovich Olga Dolinina Alexander Brovko Vitaly Pechenkin Alexey Lvov Vadim Zhmud Igor BessmertnyThis book is based on the accepted research papers presented in the International Conference "Artificial Intelligence in Engineering & Science" (AIES-2022). The aim of the AIES Conference is to bring together researchers involved in the theory of computational intelligence, knowledge engineering, fuzzy systems, soft computing, machine learning and related areas and applications in engineering, bioinformatics, industry, medicine, energy, smart city, social spheres and other areas. This book presents new perspective research results: models, methods, algorithms and applications in the field of Artificial Intelligence (AI). Particular emphasis is given to the medical applications - medical images recognition, development of the expert systems which could be interesting for the AI researchers as well for the physicians looking for the new ideas in medicine. The central audience of the book are researchers, industrial practitioners, students specialized in the Artificial Intelligence.
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)
by Juan Romero Tiago Martins Nereida Rodríguez-FernándezThis 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 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)
by Colin Johnson Nereida Rodríguez-Fernández Sérgio M. RebeloThis 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: 13th International Conference, EvoMUSART 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings (Lecture Notes in Computer Science #14633)
by Colin Johnson Sérgio M. Rebelo Iria SantosThis 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: 14th International Conference, EvoMUSART 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23–25, 2025, Proceedings (Lecture Notes in Computer Science #15611)
by Penousal Machado Colin Johnson Iria SantosThis book constitutes the refereed proceedings of the 14th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2025, held as part of EvoStar 2025, in Trieste, Itlay, during April 23–25, 2024. The 28 full papers presented in this book were carefully reviewed and selected from 52 submissions. They present a broad selection of topics and applications, including systems that create music, art, and design.
Artificial Intelligence in Music, Sound, Art and Design: 9th International Conference, EvoMUSART 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings (Lecture Notes in Computer Science #12103)
by João Correia Anikó Ekárt Juan Romero Tiago MartinsThis book constitutes the refereed proceedings of the 9th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EuroGP, EvoCOP and EvoApplications.The 15 revised full papers presented were carefully reviewed and selected from 31 submissions. The papers cover a wide spectrum of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.
Artificial Intelligence in Orthopaedic Surgery Made Easy
by Filippo Familiari Olimpio Galasso Giorgio GaspariniThis book is an essential reference guide for the use of artificial intelligence in orthopaedic surgery. It covers all related topics, from machine and deep learning, through practical applications in all orthopaedic sub-disciplines, to ethical issues and potential risks. International renowned experts equip the reader with solid scientific foundations and practical tips combining accurate literature reviews with high-quality original images. Addressing a hot topic for the present and next generation of medical specialists, this book is a must read for orthopaedic surgeons, radiologists and health informatic specialists alike.
Artificial Intelligence in Prescriptive Analytics: Innovations in Decision Analysis, Intelligent Optimization, and Data-Driven Decisions (Intelligent Systems Reference Library #260)
by Witold Pedrycz Eduardo Fernández Gilberto Rivera Gustavo Javier MeschinoConsidering 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!
Artificial Intelligence in Project Management and Making Decisions (Studies in Computational Intelligence #1035)
by Janusz Kacprzyk Pedro Y. Piñero Pérez Rafael E. Bello PérezThis book presents new developments and advances in the theory, applications, and design methods of computational intelligence, integrated in various areas of project management and BIM environments. The chapters of the book span different soft computing techniques, such as: linguistic data summarization, fuzzy systems, evolutionary algorithms, estimation distribution algorithms, computing with words, augmented reality, and hybrid intelligence systems. In addition, different applications of the neutrosophic theory are presented for the treatment of uncertainty and indeterminacy in decision-making processes. Several chapters of the book constitute systematic reviews, useful for future investigations in the following topics: linguistic summarization of data, augmented reality, and the development of BIM technologies. It is a particularly interesting book for engineers, researchers, specialists, teachers, and students related to project management and the development of BIM technologies.
Artificial Intelligence in Radiation Oncology and Biomedical Physics (Imaging in Medical Diagnosis and Therapy)
by Lei Xing Gilmer ValdesThis 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 in Renewable Energetic Systems: Smart Sustainable Energy Systems (Lecture Notes In Networks And Systems #35)
by Mustapha HattiThis book includes the latest research presented at the International Conference on Artificial Intelligence in Renewable Energetic Systems held in Tipaza, Algeria on October 22–24, 2017. The development of renewable energy at low cost must necessarily involve the intelligent optimization of energy flows and the intelligent balancing of production, consumption and energy storage. Intelligence is distributed at all levels and allows information to be processed to optimize energy flows according to constraints. This thematic is shaping the outlines of future economies of and offers the possibility of transforming society. Taking advantage of the growing power of the microprocessor makes the complexity of renewable energy systems accessible, especially since the algorithms of artificial intelligence make it possible to take relevant decisions or even reveal unsuspected trends in the management and optimization of renewable energy flows. The book enables those working on energy systems and those dealing with models of artificial intelligence to combine their knowledge and their intellectual potential for the benefit of the scientific community and humanity.
Artificial Intelligence in STEM Education: The Paradigmatic Shifts in Research, Education, and Technology (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Fan Ouyang, Pengcheng Jiao, Bruce M. McLaren and Amir H. AlaviArtificial intelligence (AI) opens new opportunities for STEM education in K-12, higher education, and professional education contexts. This book summarizes AI in education (AIED) with a particular focus on the research, practice, and technological paradigmatic shifts of AIED in recent years. The 23 chapters in this edited collection track the paradigmatic shifts of AIED in STEM education, discussing how and why the paradigms have shifted, explaining how and in what ways AI techniques have ensured the shifts, and envisioning what directions next-generation AIED is heading in the new era. As a whole, the book illuminates the main paradigms of AI in STEM education, summarizes the AI-enhanced techniques and applications used to enable the paradigms, and discusses AI-enhanced teaching, learning, and design in STEM education. It provides an adapted educational policy so that practitioners can better facilitate the application of AI in STEM education. This book is a must-read for researchers, educators, students, designers, and engineers who are interested in the opportunities and challenges of AI in STEM education.
Artificial Intelligence in Schools: A Guide for Teachers, Administrators, and Technology Leaders
by Varun AroraArtificial Intelligence in Schools is the first book to explore the use of Artificial Intelligence (AI) as a tool to enhance K–12 instruction and administration. Every industry and sector will be drastically affected by the presence of artificial intelligence, and schooling is no exception! Written for the in-service community—leaders, administrators, coaches, and teachers alike—this is your one-stop opportunity to make sure you don’t fall behind the fast pace and promising innovations of today’s most advanced learning technology. Author Varun Arora presents AI as a problem-solving tool for teaching and learning, exploring its potential and application in real-world school contexts and in the language of educators. Covering curriculum development, feedback and scoring, student empowerment, behavioral and classroom management, college readiness, and more, the book is full of novel insights and concrete, strategic takeaways.