Ai Implementation In Radiology
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Artificial Intelligence In Medical Imaging
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Author : Erik R. Ranschaert
language : en
Publisher: Springer
Release Date : 2019-01-29
Artificial Intelligence In Medical Imaging written by Erik R. Ranschaert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Medical categories.
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 implicationsfor 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.
Ai Implementation In Radiology
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Author : Erik Ranschaert
language : en
Publisher: Springer Nature
Release Date : 2024-11-26
Ai Implementation In Radiology written by Erik Ranschaert and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-26 with Medical categories.
This book describes change management in the context of implementing AI in medicine and radiology. Why do many medical institutions struggle to use AI in their clinical practice? What are the essential steps for and before an effective implementation of AI in radiology workflow? How can AI implementation trigger enduring improvements in the clinical process? The book shows how change management is crucial to effectively introduce AI to medicine and radiology, transform healthcare delivery and ensure a smooth transition while maximizing the benefits of AI and minimizing potential disruptions. Change management in the context of AI in medicine and radiology involves a systematic approach to identify, plan, implement, and evaluate the integration of AI technologies into healthcare systems. It engages the necessary stakeholders at the appropriate points in the process to ensure that change is implemented properly. By effectively managing the change, healthcare organizations can harness the potential of AI to enhance patient care, improve diagnosis accuracy, and optimize operational efficiency in radiology and other medical specialties. Throughout this change management process, organizations should prioritize ethical considerations, data privacy, and regulatory compliance to ensure that AI technologies are deployed responsibly and in accordance with relevant guidelines and regulations.
The Future Of The Professions
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Author : Richard E. Susskind
language : en
Publisher: Oxford University Press
Release Date : 2022
The Future Of The Professions written by Richard E. Susskind and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Business & Economics categories.
With a new preface outlining the most recent critical developments, this updated edtion of The Future of the Professions predicts how technology will transform the work of doctors, teachers, architects, lawyers, and many others in the 21st century, and introduces the people and systems that may replace them.
The Impact Of Artificial Intelligence In Radiology
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Author : Adam E. M. Eltorai
language : en
Publisher: CRC Press
Release Date : 2024-12-27
The Impact Of Artificial Intelligence In Radiology written by Adam E. M. Eltorai and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Medical categories.
Implementation of artificial intelligence (AI) in radiology is an important topic of discussion. Advances in AI—which encompass machine learning, artificial neural networks, and deep learning—are increasingly being applied to diagnostic imaging. While some posit radiologists are irreplaceable, certain AI proponents have proposed to "stop training radiologists now." By compiling perspectives from experts from various backgrounds, this book explores the current state of AI efforts in radiology along with the clinical, financial, technological, and societal perspectives on the role and expected impact of AI in radiology.
Discourse Dynamics
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Author : Ian Parker
language : en
Publisher: Routledge
Release Date : 2014-01-27
Discourse Dynamics written by Ian Parker and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-27 with Psychology categories.
What are discourses? Are discourses ‘real’, and what is real outside language? In this book, originally published in 1992, Ian Parker provides one of the clearest and most systematic introductions to discourse research and the essential theoretical debates in the area. At the time it was one of the few texts to defend a realist position, discuss accounts of postmodernity and set out criteria for the identification of discourses. Discourse Dynamics is essential reading to anyone interested in project research and an understanding of the theoretical issues involved in discourse analysis. The book will also be of use to students other than those studying psychology. It addresses the concerns of all those looking at qualitative textual research in the human sciences and is still very much relevant today.
Healthcare And Artificial Intelligence
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Author : Bernard Nordlinger
language : en
Publisher: Springer Nature
Release Date : 2020-03-17
Healthcare And Artificial Intelligence written by Bernard Nordlinger and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-17 with Technology & Engineering categories.
This book provides an overview of the role of AI in medicine and, more generally, of issues at the intersection of mathematics, informatics, and medicine. It is intended for AI experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious about this timely and important subject. Its goal is to provide clear, objective, and reasonable information on the issues covered, avoiding any fantasies that the topic “AI” might evoke. In addition, the book seeks to provide a broad kaleidoscopic perspective, rather than deep technical details.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
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
Artificial Intelligence And Machine Learning In 2d 3d Medical Image Processing
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Author : Rohit Raja
language : en
Publisher: CRC Press
Release Date : 2020-12-23
Artificial Intelligence And Machine Learning In 2d 3d Medical Image Processing written by Rohit Raja and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-23 with Technology & Engineering categories.
Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field
Web Survey Methodology
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Author : Mario Callegaro
language : en
Publisher: SAGE
Release Date : 2015-04-30
Web Survey Methodology written by Mario Callegaro and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-30 with Social Science categories.
Web Survey Methodology guides the reader through the past fifteen years of research in web survey methodology. It both provides practical guidance on the latest techniques for collecting valid and reliable data and offers a comprehensive overview of research issues. Core topics from preparation to questionnaire design, recruitment testing to analysis and survey software are all covered in a systematic and insightful way. The reader will be exposed to key concepts and key findings in the literature, covering measurement, non-response, adjustments, paradata, and cost issues. The book also discusses the hottest research topics in survey research today, such as internet panels, virtual interviewing, mobile surveys and the integration with passive measurements, e-social sciences, mixed modes and business intelligence. The book is intended for students, practitioners, and researchers in fields such as survey and market research, psychological research, official statistics and customer satisfaction research.
Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala