Machine Learning And Ai In Clinical Practice

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Artificial Intelligence in Healthcare

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Deep Medicine

Author : Eric Topol
Publisher : Basic Books
ISBN 13 : 1541644646
Total Pages : 373 pages
Book Rating : 4.5/5 (416 download)

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Book Synopsis Deep Medicine by : Eric Topol

Download or read book Deep Medicine written by Eric Topol and published by Basic Books. This book was released on 2019-03-12 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Artificial Intelligence in Medicine

Author : David Riaño
Publisher : Springer
ISBN 13 : 303021642X
Total Pages : 431 pages
Book Rating : 4.0/5 (32 download)

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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.

Machine Learning and AI for Healthcare

Author : Arjun Panesar
Publisher : Apress
ISBN 13 : 1484237994
Total Pages : 390 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Machine Learning and AI for Healthcare by : Arjun Panesar

Download or read book Machine Learning and AI for Healthcare written by Arjun Panesar and published by Apress. This book was released on 2019-02-04 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

Artificial Intelligence in Medical Imaging

Author : Lia Morra
Publisher : CRC Press
ISBN 13 : 1000753085
Total Pages : 165 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Artificial Intelligence in Medical Imaging by : Lia Morra

Download or read book Artificial Intelligence in Medical Imaging written by Lia Morra and published by CRC Press. This book was released on 2019-11-25 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Choice 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 and Machine Learning in Healthcare

Author : Ankur Saxena
Publisher : Springer Nature
ISBN 13 : 9811608113
Total Pages : 228 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Artificial Intelligence and Machine Learning in Healthcare by : Ankur Saxena

Download or read book Artificial Intelligence and Machine Learning in Healthcare written by Ankur Saxena and published by Springer Nature. This book was released on 2021-05-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.

Deep Learning in Healthcare

Author : Yen-Wei Chen
Publisher : Springer Nature
ISBN 13 : 3030326063
Total Pages : 225 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Deep Learning in Healthcare by : Yen-Wei Chen

Download or read book Deep Learning in Healthcare written by Yen-Wei Chen and published by Springer Nature. This book was released on 2019-11-18 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.

Machine Learning and AI in Clinical Practice

Author : Herman Strange
Publisher : Rise of Cognitive Computing: AI Evolution from Origins to Adoption
ISBN 13 : 9782231913557
Total Pages : 0 pages
Book Rating : 4.9/5 (135 download)

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Book Synopsis Machine Learning and AI in Clinical Practice by : Herman Strange

Download or read book Machine Learning and AI in Clinical Practice written by Herman Strange and published by Rise of Cognitive Computing: AI Evolution from Origins to Adoption. This book was released on 2023-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and AI in Clinical Practice: Revolutionizing Diagnosis and Treatment Strategies is a groundbreaking book that delves into the world of artificial intelligence (AI) and machine learning (ML) in healthcare. With advancements in technology, AI and ML have become integral parts of clinical practice, revolutionizing the way diagnoses are made and treatments are administered. This book provides a comprehensive overview of the latest AI and ML applications in healthcare, offering a glimpse into the future of medicine. From predicting treatment outcomes and identifying patient risk factors to drug discovery and personalized medicine, the potential applications of AI and ML in healthcare are limitless. The authors, a team of leading experts in the field, explore the benefits and challenges of using AI and ML in clinical practice, and provide valuable insights into the ethical and social considerations of this rapidly-evolving technology. They also discuss the potential impact on healthcare operations and the need for continued research and development to ensure the responsible use of AI and ML in medicine. Whether you are a healthcare professional, a researcher, or simply interested in the future of medicine, Machine Learning and AI in Clinical Practice is an essential guide to understanding the latest advancements in this exciting field. With detailed explanations of key concepts and real-world case studies, this book is both informative and accessible. Don't miss out on the opportunity to learn about the latest developments in AI and ML in healthcare. This book is a must-read for anyone interested in the future of medicine and the potential for technology to revolutionize clinical practice. Order your copy today and discover the endless possibilities of AI and ML in healthcare.

AI-First Healthcare

Author : Kerrie L. Holley
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492063126
Total Pages : 222 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis AI-First Healthcare by : Kerrie L. Holley

Download or read book AI-First Healthcare written by Kerrie L. Holley and published by "O'Reilly Media, Inc.". This book was released on 2021-04-19 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI is poised to transform every aspect of healthcare, including the way we manage personal health, from customer experience and clinical care to healthcare cost reductions. This practical book is one of the first to describe present and future use cases where AI can help solve pernicious healthcare problems. Kerrie Holley and Siupo Becker provide guidance to help informatics and healthcare leadership create AI strategy and implementation plans for healthcare. With this book, business stakeholders and practitioners will be able to build knowledge, a roadmap, and the confidence to support AIin their organizations—without getting into the weeds of algorithms or open source frameworks. Cowritten by an AI technologist and a medical doctor who leverages AI to solve healthcare’s most difficult challenges, this book covers: The myths and realities of AI, now and in the future Human-centered AI: what it is and how to make it possible Using various AI technologies to go beyond precision medicine How to deliver patient care using the IoT and ambient computing with AI How AI can help reduce waste in healthcare AI strategy and how to identify high-priority AI application

Artificial Intelligence in Clinical Practice

Author : Chayakrit Krittanawong
Publisher : Elsevier
ISBN 13 : 0443156891
Total Pages : 550 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Artificial Intelligence in Clinical Practice by : Chayakrit Krittanawong

Download or read book Artificial Intelligence in Clinical Practice written by Chayakrit Krittanawong and published by Elsevier. This book was released on 2023-09-29 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles current research on Artificial Intelligence within medical subspecialties, helping practitioners with diagnosis, clinical decision-making, disease prediction, prevention, and the facilitation of precision medicine. The book defines the basic concepts of big data and AI in medicine and highlights current applications, challenges, ethical issues, and biases. Each chapter discusses AI applied to a specific medical subspecialty, including primary care, preventive medicine, general internal medicine, radiology, pathology, infectious disease, gastroenterology, cardiology, hematology, oncology, dermatology, ophthalmology, mental health, neurology, pulmonary, critical care, rheumatology, surgery, and OB-GYN. This is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested in learning more about artificial intelligence technologies and their applications in medicine. Provides the history and overview of the various modalities of AI and their applications within each field of medicine Discusses current AI-based medical research, including landmark trials within each field of medicine Addresses the current knowledge gaps that clinicians commonly face that prevent the application of AI-based research to clinical practice Encompasses examples of specific cases and discusses challenges and biases associated with AI

Artificial Intelligence and Machine Learning in Public Healthcare

Author : KC Santosh
Publisher : Springer Nature
ISBN 13 : 9811667683
Total Pages : 93 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Artificial Intelligence and Machine Learning in Public Healthcare by : KC Santosh

Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh and published by Springer Nature. This book was released on 2022-01-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Artificial Intelligence and Deep Learning in Pathology

Author : Stanley Cohen
Publisher : Elsevier Health Sciences
ISBN 13 : 0323675379
Total Pages : 290 pages
Book Rating : 4.3/5 (236 download)

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Book Synopsis Artificial Intelligence and Deep Learning in Pathology by : Stanley Cohen

Download or read book Artificial Intelligence and Deep Learning in Pathology written by Stanley Cohen and published by Elsevier Health Sciences. This book was released on 2020-06-02 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.

Artificial Intelligence

Author : Sandeep Reddy
Publisher : CRC Press
ISBN 13 : 1000216861
Total Pages : 287 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Artificial Intelligence by : Sandeep Reddy

Download or read book Artificial Intelligence written by Sandeep Reddy and published by CRC Press. This book was released on 2020-12-02 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery. Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.

Practical AI for Healthcare Professionals

Author : Abhinav Suri
Publisher : Apress
ISBN 13 : 9781484277799
Total Pages : 254 pages
Book Rating : 4.2/5 (777 download)

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Book Synopsis Practical AI for Healthcare Professionals by : Abhinav Suri

Download or read book Practical AI for Healthcare Professionals written by Abhinav Suri and published by Apress. This book was released on 2021-12-14 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical AI for Healthcare Professionals Artificial Intelligence (AI) is a buzzword in the healthcare sphere today. However, notions of what AI actually is and how it works are often not discussed. Furthermore, information on AI implementation is often tailored towards seasoned programmers rather than the healthcare professional/beginner coder. This book gives an introduction to practical AI in the medical sphere, focusing on real-life clinical problems, how to solve them with actual code, and how to evaluate the efficacy of those solutions. You’ll start by learning how to diagnose problems as ones that can and cannot be solved with AI. You’ll then learn the basics of computer science algorithms, neural networks, and when each should be applied. Then you’ll tackle the essential parts of basic Python programming relevant to data processing and making AI programs. The Tensorflow/Keras library along with Numpy and Scikit-Learn are covered as well. Once you’ve mastered those basic computer science and programming concepts, you can dive into projects with code, implementation details, and explanations. These projects give you the chance to explore using machine learning algorithms for issues such as predicting the probability of hospital admission from emergency room triage and patient demographic data. We will then use deep learning to determine whether patients have pneumonia using chest X-Ray images. The topics covered in this book not only encompass areas of the medical field where AI is already playing a major role, but also are engineered to cover as much as possible of AI that is relevant to medical diagnostics. Along the way, readers can expect to learn data processing, how to conceptualize problems that can be solved by AI, and how to program solutions to those problems. Physicians and other healthcare professionals who can master these skills will be able to lead AI-based research and diagnostic tool development, ultimately benefiting countless patients.

Artificial Intelligence in Healthcare

Author : Parag Mahajan
Publisher : Medmantra, LLC
ISBN 13 : 9781954612020
Total Pages : 628 pages
Book Rating : 4.6/5 (12 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Parag Mahajan

Download or read book Artificial Intelligence in Healthcare written by Parag Mahajan and published by Medmantra, LLC. This book was released on 2021-02 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: ① Do you know what AI is doing to improve our health and wellbeing? ② Does this new technology concern you, or impress you? ③ Do you want to know more about the future of AI in healthcare? Technology continues to advance at a pace that can seem bewildering. Nowhere else is it moving faster than in the health sector, where ♥AI is now being used to improve millions of lives♥. In this book, ◆ Artificial Intelligence in Healthcare: AI, Machine Learning, and Deep and Intelligent Medicine Simplified for Everyone ◆, you can discover the great improvements that AI is making, with chapters covering: The current applications and future of AI in healthcare and all major medical specialties ✓ The benefits and risks weighed up ✓ The ethics involved ✓ Machine learning and data science simplified ✓ AI's role in medical research and education, health insurance, drug discovery, electronic health records, and the fight against COVID-19 ✓ The roles that major corporations and start-up companies are playing ✓ The implementation of AI in clinical practice ✓ And lots more... Quite simply the most authoritative text on the subject, Artificial Intelligence in Healthcare - 3rd Edition, is an absorbing and compelling read for anyone who wants to know more. It is packed with more updated information than any other book currently available, written in easy-to-understand language, and accessible to all.

Machine Learning and the Internet of Medical Things in Healthcare

Author : Krishna Kant Singh
Publisher : Academic Press
ISBN 13 : 012823217X
Total Pages : 290 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Machine Learning and the Internet of Medical Things in Healthcare by : Krishna Kant Singh

Download or read book Machine Learning and the Internet of Medical Things in Healthcare written by Krishna Kant Singh and published by Academic Press. This book was released on 2021-04-14 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Artificial Intelligence in Medical Imaging

Author : Erik R. Ranschaert
Publisher : Springer
ISBN 13 : 3319948784
Total Pages : 373 pages
Book Rating : 4.3/5 (199 download)

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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 373 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.