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Explainable Artificial Intelligence And Process Mining Applications For Healthcare
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Book Synopsis Explainable Artificial Intelligence and Process Mining Applications for Healthcare by : Jose M. Juarez
Download or read book Explainable Artificial Intelligence and Process Mining Applications for Healthcare written by Jose M. Juarez and published by Springer Nature. This book was released on with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Process Mining in Healthcare by : Ronny S. Mans
Download or read book Process Mining in Healthcare written by Ronny S. Mans and published by Springer. This book was released on 2015-03-12 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are the possibilities for process mining in hospitals? In this book the authors provide an answer to this question by presenting a healthcare reference model that outlines all the different classes of data that are potentially available for process mining in healthcare and the relationships between them. Subsequently, based on this reference model, they explain the application opportunities for process mining in this domain and discuss the various kinds of analyses that can be performed. They focus on organizational healthcare processes rather than medical treatment processes. The combination of event data and process mining techniques allows them to analyze the operational processes within a hospital based on facts, thus providing a solid basis for managing and improving processes within hospitals. To this end, they also explicitly elaborate on data quality issues that are relevant for the data aspects of the healthcare reference model. This book mainly targets advanced professionals involved in areas related to business process management, business intelligence, data mining, and business process redesign for healthcare systems as well as graduate students specializing in healthcare information systems and process analysis.
Book Synopsis Advances in Smart Healthcare Paradigms and Applications by : Halina Kwaśnicka
Download or read book Advances in Smart Healthcare Paradigms and Applications written by Halina Kwaśnicka and published by Springer Nature. This book was released on 2023-08-16 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to showcase research and innovation in smart healthcare systems and technologies led by women scientists, researchers, and practitioners. With the advent of artificial intelligence (AI) and related technologies, the healthcare sector has undergone tremendous changes in practice and management in recent years. On par to men, women have made significant contributions to tackle a variety of healthcare problems, creating smarter paradigms to provide effective and efficient solutions for patients and stakeholders. The book presents a small collection of contributions by outstanding women in STEM (Science, Technology, Engineering and Mathematics) education, focusing on the healthcare domain. The selected articles allow readers to comprehend current advances in AI and other methods for undertaking healthcare challenges. It is envisaged that the inspiring work by prominent women scientists, researchers, and practitioners reported in this book offers a beacon to propel women in pursuing STEM education and advancing the healthcare sector for the benefits of humankind.
Book Synopsis Convergence of Blockchain and Explainable Artificial Intelligence by : Akansha Singh
Download or read book Convergence of Blockchain and Explainable Artificial Intelligence written by Akansha Singh and published by CRC Press. This book was released on 2024-10-30 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explainable AI (XAI) is an upcoming research field in the domain of machine learning. This book aims to provide a detailed description of the topics related to XAI and Blockchain. These two technologies can benefit each other, and the research outcomes will benefit society in multiple ways. Existing AI systems make decisions in a black box manner. Explainable AI delineates how an AI system arrived at a particular decision. It inspects the steps and models that are responsible for making a particular decision. It is an upcoming trend that aims at providing explanations to the AI decisions. Blockchain is emerging as an effective technique for XAI. It enables accessibility to digital ledgers amongst the various AI agents. The AI agents collaborate using consensus and decisions are saved on Blocks. These blocks can be traced back but cannot be changed. Thus, the combination of AI with blockchain provides transparency and visibility to all AI decisions. BlockXAI is also being widely used for improving data security and intelligence. The decisions made are consensus based and decentralized leading to highly efficient AI systems. This book also covers topics that present the convergence of Blockchain with explainable AI and will provide researchers, academics, and industry experts with a complete guide to BlockXAI.
Book Synopsis Interactive Process Mining in Healthcare by : Carlos Fernandez-Llatas
Download or read book Interactive Process Mining in Healthcare written by Carlos Fernandez-Llatas and published by Springer Nature. This book was released on 2020-10-28 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a practically applicable guide to the methodologies and technologies for the application of interactive process mining paradigm. Case studies are presented where this paradigm has been successfully applied in emergency medicine, surgery processes, human behavior modelling, strokes and outpatients’ services, enabling the reader to develop a deep understanding of how to apply process mining technologies in healthcare to support them in inferring new knowledge from past actions, and providing accurate and personalized knowledge to improve their future clinical decision-making. Interactive Process Mining in Healthcare comprehensively covers how machine learning algorithms can be utilized to create real scientific evidence to improve daily healthcare protocols, and is a valuable resource for a variety of health professionals seeking to develop new methods to improve their clinical decision-making.
Book Synopsis Artificial Intelligence in Medicine by : Jose M. Juarez
Download or read book Artificial Intelligence in Medicine written by Jose M. Juarez and published by Springer Nature. This book was released on 2023-06-04 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Explainable Machine Learning for Multimedia Based Healthcare Applications by : M. Shamim Hossain
Download or read book Explainable Machine Learning for Multimedia Based Healthcare Applications written by M. Shamim Hossain and published by Springer Nature. This book was released on with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Explainable Artificial Intelligence for Smart Cities by : Mohamed Lahby
Download or read book Explainable Artificial Intelligence for Smart Cities written by Mohamed Lahby and published by CRC Press. This book was released on 2021-11-09 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future. The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become ‘black-box’ to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.
Book Synopsis Explainable Artificial Intelligence for Biomedical and Healthcare Applications by : Aditya Khamparia
Download or read book Explainable Artificial Intelligence for Biomedical and Healthcare Applications written by Aditya Khamparia and published by CRC Press. This book was released on 2024-10-09 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference text helps us understand how the concepts of explainable artificial intelligence (XAI) are used in the medical and healthcare sectors. The text discusses medical robotic systems using XAI and physical devices having autonomous behaviors for medical operations. It explores the usage of XAI for analyzing different types of unique data sets for medical image analysis, medical image registration, medical data synthesis, and information discovery. It covers important topics including XAI for biometric security, genomics, and medical disease diagnosis. This book: • Provides an excellent foundation for the core concepts and principles of explainable AI in biomedical and healthcare applications. • Covers explainable AI for robotics and autonomous systems. • Discusses usage of explainable AI in medical image analysis, medical image registration, and medical data synthesis. • Examines biometrics security-assisted applications and their integration using explainable AI. The text will be useful for graduate students, professionals, and academic researchers in diverse areas such as electrical engineering, electronics and communication engineering, biomedical engineering, and computer science.
Book Synopsis Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by : Wojciech Samek
Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Book Synopsis Artificial Intelligence in Healthcare by : Tianhua Chen
Download or read book Artificial Intelligence in Healthcare written by Tianhua Chen and published by Springer Nature. This book was released on 2022-10-25 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in artificial intelligence (AI) and machine learning have witnessed many successes in various disciplines including the healthcare sector. Innovations in intelligent medical systems have revolutionized the way in which healthcare services are provided, ranging from making clinical diagnosis, developing personalized treatment and drugs, assisting patient monitoring, to automating administrative tasks and reducing operational costs. In this book, the authors present key applications in the general area of health care, where AI has made significant successes. From the individual chapters, the readers will be provided with a range of examples to illustrate the wide plethora of application domains utilizing state-of-the-art AI techniques, proving credence to the versatility and effectiveness of an AI approach in health care and medicine. We envisage that this book is ideal for individuals new to the notion of AI in health care, equally, early career academics who wish to further expand on their knowledge in AI in medicine. What will be presented is in no means an exhaustive list of applications, but most definitely a varied one.
Book Synopsis Smart and Healthy Walking by : Tin-Chih Toly Chen
Download or read book Smart and Healthy Walking written by Tin-Chih Toly Chen and published by Springer Nature. This book was released on with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Medical Data Analysis and Processing using Explainable Artificial Intelligence by : Om Prakash Jena
Download or read book Medical Data Analysis and Processing using Explainable Artificial Intelligence written by Om Prakash Jena and published by CRC Press. This book was released on 2023-11-06 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical Presents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing Discusses machine learning and deep learning scalability models in healthcare systems This text focuses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.
Book Synopsis Explainable Artificial Intelligence (XAI) in Manufacturing by : Tin-Chih Toly Chen
Download or read book Explainable Artificial Intelligence (XAI) in Manufacturing written by Tin-Chih Toly Chen and published by Springer Nature. This book was released on 2023-03-16 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the latest developments in Explainable AI (XAI) and its applications in manufacturing. It covers the various methods, tools, and technologies that are being used to make AI more understandable and communicable for factory workers. With the increasing use of AI in manufacturing, there is a growing need to address the limitations of advanced AI methods that are difficult to understand or explain to those without a background in AI. This book addresses this need by providing a systematic review of the latest research and advancements in XAI specifically tailored for the manufacturing industry. The book includes real-world case studies and examples to illustrate the practical applications of XAI in manufacturing. It is a valuable resource for researchers, engineers, and practitioners working in the field of AI and manufacturing.
Book Synopsis Advanced Computational Intelligence in Healthcare-7 by : Ilias Maglogiannis
Download or read book Advanced Computational Intelligence in Healthcare-7 written by Ilias Maglogiannis and published by Springer Nature. This book was released on 2020-03-23 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art works and systematic reviews in the emerging field of computational intelligence (CI) in electronic health care. The respective chapters present surveys and practical examples of artificial intelligence applications in the areas of Human-Machine Interface (HMI) and affective computing, machine learning, big health data and visualization analytics, computer vision and medical image analysis. The book also addresses new and emerging topics in CI for health care such as the utilization of Social Media (SM) and the introduction of new intelligent paradigms in the security and privacy domains, which are critical for the health sector. The chapters, while of course not exhaustively addressing all the possible aspects of the aforementioned areas, are indicative of the dynamic nature of interdisciplinary research being pursued. Accordingly, the book is intended not only for researchers in the respective fields, but also for medical and administrative personnel working in the health sector, as well as managers and stakeholders responsible for making strategic decisions and defining public health policies.
Book Synopsis Artificial Intelligence in Medicine by : David Riaño
Download or read book Artificial Intelligence in Medicine written by David Riaño and published by Springer. This book was released on 2019-06-19 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Artificial Intelligence in Medical Imaging by : Erik R. Ranschaert
Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
