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Explainable Artificial Intelligence For Biomedical And Healthcare Applications
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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 . This book was released on 2024-10-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference text helps 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 behaviours for medical operations. It explores the usage of XAI for analysing 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 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 Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI) by : Aditya Khamparia
Download or read book Biomedical Data Analysis and Processing Using Explainable (XAI) and Responsive Artificial Intelligence (RAI) written by Aditya Khamparia and published by Springer Nature. This book was released on 2022-04-09 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. It will discuss the advantages in dealing with big and complex data by using explainable AI concepts in the field of biomedical sciences. The book explains both positive as well as negative findings obtained by explainable AI techniques. It features real time experiences by physicians and medical staff for applied deep learning based solutions. The book will be extremely useful for researchers and practitioners in advancing their studies.
Book Synopsis Deep Learning in Gaming and Animations by : Vikas Chaudhary
Download or read book Deep Learning in Gaming and Animations written by Vikas Chaudhary and published by CRC Press. This book was released on 2021-12-07 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine translation, natural language understanding, and computer vision. As a result, computers can now achieve human-competitive performance in a wide range of perception and recognition tasks. Many of these systems are now available to the programmer via a range of so-called cognitive services. More recently, deep reinforcement learning has achieved ground-breaking success in several complex challenges. This book makes an enormous contribution to this beautiful, vibrant area of study: an area that is developing rapidly both in breadth and depth. Deep learning can cope with a broader range of tasks (and perform those tasks to increasing levels of excellence). This book lays a good foundation for the core concepts and principles of deep learning in gaming and animation, walking you through the fundamental ideas with expert ease. This book progresses in a step-by-step manner. It reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into its applications. Also, some chapters introduce and cover novel ideas about how artificial intelligence (AI), deep learning, and machine learning have changed the world in gaming and animation. It gives us the idea that AI can also be applied in gaming, and there are limited textbooks in this area. This book comprehensively addresses all the aspects of AI and deep learning in gaming. Also, each chapter follows a similar structure so that students, teachers, and industry experts can orientate themselves within the text. There are few books in the field of gaming using AI. Deep Learning in Gaming and Animations teaches you how to apply the power of deep learning to build complex reasoning tasks. After being exposed to the foundations of machine and deep learning, you will use Python to build a bot and then teach it the game's rules. This book also focuses on how different technologies have revolutionized gaming and animation with various illustrations.
Book Synopsis Medical Data Analysis and Processing Using Explainable Artificial Intelligence by :
Download or read book Medical Data Analysis and Processing Using Explainable Artificial Intelligence written by and published by . This book was released on 2023 with total page 0 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 AI in Healthcare and Medicine by : Arash Shaban-Nejad
Download or read book Explainable AI in Healthcare and Medicine written by Arash Shaban-Nejad and published by Springer Nature. This book was released on 2020-11-02 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.
Book Synopsis Explainable Artificial Intelligence for Biomedical Applications by : Utku Kose
Download or read book Explainable Artificial Intelligence for Biomedical Applications written by Utku Kose and published by CRC Press. This book was released on 2023-12-14 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its first appearance, artificial intelligence has been ensuring revolutionary outcomes in the context of real-world problems. At this point, it has strong relations with biomedical and today’s intelligent systems compete with human capabilities in medical tasks. However, advanced use of artificial intelligence causes intelligent systems to be black-box. That situation is not good for building trustworthy intelligent systems in medical applications. For a remarkable amount of time, researchers have tried to solve the black-box issue by using modular additions, which have led to the rise of the term: interpretable artificial intelligence. As the literature matured (as a result of, in particular, deep learning), that term transformed into explainable artificial intelligence (XAI). This book provides an essential edited work regarding the latest advancements in explainable artificial intelligence (XAI) for biomedical applications. It includes not only introductive perspectives but also applied touches and discussions regarding critical problems as well as future insights. Topics discussed in the book include: XAI for the applications with medical images XAI use cases for alternative medical data/task Different XAI methods for biomedical applications Reviews for the XAI research for critical biomedical problems. Explainable Artificial Intelligence for Biomedical Applications is ideal for academicians, researchers, students, engineers, and experts from the fields of computer science, biomedical, medical, and health sciences. It also welcomes all readers of different fields to be informed about use cases of XAI in black-box artificial intelligence. In this sense, the book can be used for both teaching and reference source purposes.
Book Synopsis Explainable AI in Healthcare by : Mehul S Raval
Download or read book Explainable AI in Healthcare written by Mehul S Raval and published by CRC Press. This book was released on 2023-07-17 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care
Book Synopsis Principles and Methods of Explainable Artificial Intelligence in Healthcare by : Albuquerque, Victor Hugo C. de
Download or read book Principles and Methods of Explainable Artificial Intelligence in Healthcare written by Albuquerque, Victor Hugo C. de and published by IGI Global. This book was released on 2022-05-20 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model’s adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.
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 (XAI) in Healthcare by : Utku Kose
Download or read book Explainable Artificial Intelligence (XAI) in Healthcare written by Utku Kose and published by CRC Press. This book was released on 2024-04-23 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the use of explainable artificial intelligence (XAI) for healthcare problems, in order to improve trustworthiness, performance and sustainability levels in the context of applications. Explainable Artificial Intelligence (XAI) in Healthcare adopts the understanding that AI solutions should not only have high accuracy performance, but also be transparent, understandable and reliable from the end user's perspective. The book discusses the techniques, frameworks, and tools to effectively implement XAI methodologies in critical problems of healthcare field. The authors offer different types of solutions, evaluation methods and metrics for XAI and reveal how the concept of explainability finds a response in target problem coverage. The authors examine the use of XAI in disease diagnosis, medical imaging, health tourism, precision medicine and even drug discovery. They also point out the importance of user perspectives and value of the data used in target problems. Finally, the authors also ensure a well-defined future perspective for advancing XAI in terms of healthcare. This book will offer great benefits to students at the undergraduate and graduate levels and researchers. The book will also be useful for industry professionals and clinicians who perform critical decision-making tasks.
Book Synopsis Applied Artificial Intelligence by : Swati V. Shinde
Download or read book Applied Artificial Intelligence written by Swati V. Shinde and published by CRC Press. This book was released on 2023-09-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems. Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images. The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.
Book Synopsis Artificial Intelligence for Healthcare Applications and Management by : Boris Galitsky
Download or read book Artificial Intelligence for Healthcare Applications and Management written by Boris Galitsky and published by Academic Press. This book was released on 2022-01-13 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for Healthcare Applications and Management introduces application domains of various AI algorithms across healthcare management. Instead of discussing AI first and then exploring its applications in healthcare afterward, the authors attack the problems in context directly, in order to accelerate the path of an interested reader toward building industrial-strength healthcare applications. Readers will be introduced to a wide spectrum of AI applications supporting all stages of patient flow in a healthcare facility. The authors explain how AI supports patients throughout a healthcare facility, including diagnosis and treatment recommendations needed to get patients from the point of admission to the point of discharge while maintaining quality, patient safety, and patient/provider satisfaction. AI methods are expected to decrease the burden on physicians, improve the quality of patient care, and decrease overall treatment costs. Current conditions affected by COVID-19 pose new challenges for healthcare management and learning how to apply AI will be important for a broad spectrum of students and mature professionals working in medical informatics. This book focuses on predictive analytics, health text processing, data aggregation, management of patients, and other fields which have all turned out to be bottlenecks for the efficient management of coronavirus patients. Presents an in-depth exploration of how AI algorithms embedded in scheduling, prediction, automated support, personalization, and diagnostics can improve the efficiency of patient treatment Investigates explainable AI, including explainable decision support and machine learning, from limited data to back-up clinical decisions, and data analysis Offers hands-on skills to computer science and medical informatics students to aid them in designing intelligent systems for healthcare Informs a broad, multidisciplinary audience about a multitude of applications of machine learning and linguistics across various healthcare fields Introduces medical discourse analysis for a high-level representation of health texts
Book Synopsis Artificial Intelligence for Health 4.0: Challenges and Applications by : Rishabha Malviya
Download or read book Artificial Intelligence for Health 4.0: Challenges and Applications written by Rishabha Malviya and published by CRC Press. This book was released on 2023-03-10 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare is one of the major success stories of our times. Medical science has improved rapidly, raising life expectancy around the world. However, as longevity increases, healthcare systems face growing demands for their services, rising costs, and a workforce that is struggling to meet the needs of its patients. Healthcare is one of the most critical sectors in the broader landscape of big data because of its fundamental role in a productive, thriving society. Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. The application of AI to healthcare data can literally be a matter of life and death. AI can assist doctors, nurses, and other healthcare workers in their daily work. AI in healthcare can enhance preventive care and quality of life, produce more accurate diagnoses and treatment plans, and lead to better patient outcomes overall. This book gives insights into the latest developments of applications of AI in biomedicine, including disease diagnostics, pharmaceutical processing, patient care and monitoring, biomedical information, and biomedical research. It also presents an outline of the recent breakthroughs in the application of AI in healthcare, describes a roadmap to building effective, reliable, and safe AI systems, and discusses the possible future direction of AI augmented healthcare systems. AI has countless applications in healthcare. Whether it’s being used to discover links between genetic codes, to power surgical robots or even to maximize hospital efficiency; AI has been a boon to the healthcare industry.
Author :Victor Hugo C. De Albuquerque Publisher :Medical Information Science Reference ISBN 13 :9781668437919 Total Pages :325 pages Book Rating :4.4/5 (379 download)
Book Synopsis Principles and Methods of Explainable Artificial Intelligence in Healthcare by : Victor Hugo C. De Albuquerque
Download or read book Principles and Methods of Explainable Artificial Intelligence in Healthcare written by Victor Hugo C. De Albuquerque and published by Medical Information Science Reference. This book was released on 2022 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the Explainable Artificial Intelligence (XAI) for healthcare, providing a broad overview of state-of-art approaches for accurate analysis and diagnosis, and encompassing computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, medical imaging data that assist in earlier prediction"--
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 Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics by : Sunil Kumar Dhal
Download or read book Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics written by Sunil Kumar Dhal and published by John Wiley & Sons. This book was released on 2022-06-28 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.
