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Artificial Intelligence And Machine Learning In Healthcare

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Applications of Artificial Intelligence and Machine Learning in Healthcare

Applications of Artificial Intelligence and Machine Learning in Healthcare Book
Author : Hassan Alamoudi
Publisher : Unknown
Release : 2019
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Artificial Intelligence (AI) is becoming a ubiquitous term that is used in many fields of research or the popular culture. Among these fields that was affected by this hype is the healthcare sector. Along with its subdomain, Machine Learning (ML), they established an environment of interest in the promises of machines versus humans capabilities. Though artificial intelligence applications in healthcare such as interpreting ECGs could date back to the mid of the twentieth century, the promises of AI still at its beginning when it comes to new breakthroughs. This is due to the transformation into a digital world and new advancements in the processing capabilities. Computer vision has contributed the most to the healthcare sector where it can leverage doctors and practitioners with automated classification and annotations as a preparing step. This kind of mechanism is the best suited for applications of AI in healthcare. However, the amount of data in other forms such as textual or lab results is exceeding the force power. While a solution could be to use machines to learn and propose solutions, the results could be catastrophic and human lives are on stake. So, explainable AI could be beneficial where it analyzes and makes predictions that can be trusted by the users. The study here is conducted on cardiovascular patients dataset to predict the presence or absence of the disease. Classifications techniques used include Nave Bayes, Logistic Regression, Decision Trees, Support Vector Machines, and Artificial Neural Networks. The Logistic regression model achieved the best Area under the curve. Moreover, an extension of the previous studies discussed is conducted to explain the model and to show how models of AI can be trusted and not used as black-boxes.

Artificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare Book
Author : Ankur Saxena,Shivani Chandra
Publisher : Springer
Release : 2021-05-25
ISBN : 9789811608100
Language : En, Es, Fr & De

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Book Description :

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.

Machine Learning and AI for Healthcare

Machine Learning and AI for Healthcare Book
Author : Arjun Panesar
Publisher : Apress
Release : 2019-02-04
ISBN : 1484237994
Language : En, Es, Fr & De

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Book Description :

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 Learn Gain 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 agents Who 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 Healthcare

Artificial Intelligence in Healthcare Book
Author : Parag Mahajan
Publisher : Unknown
Release : 2021-03-04
ISBN : 9781954612068
Language : En, Es, Fr & De

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Book Description :

About the book:? Do you know what AI is doing to improve our health and wellbeing?? Does this new technology concern you, or impress you?? 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.

Artificial Intelligence

Artificial Intelligence Book
Author : Sandeep Reddy
Publisher : CRC Press
Release : 2020-12-03
ISBN : 1000216861
Language : En, Es, Fr & De

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Book Description :

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.

Machine Intelligence for Healthcare

Machine Intelligence for Healthcare Book
Author : Francis X. Campion,Gunnar Carlsson,Francis , FACP
Publisher : Unknown
Release : 2017-02-02
ISBN : 9781542924948
Language : En, Es, Fr & De

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Book Description :

Machine Intelligence for Healthcare is a must read for physician leaders, health insurance executives, clinical researchers, public health officials, data scientists and software engineers seeking to understand this pivotal innovation in the information revolution in healthcare. MI for Healthcare provides a detailed introduction of Machine Intelligence, then takes the reader on a journey through the basics of machine learning, topological data analysis and applications of machine intelligence software for healthcare and life sciences. Over 20 case studies cover topics related to clinical variation analysis, hospital clinical pathways, population health management, genetic analysis, precision medicine, healthcare revenue cycle, and payment integrity. The book includes a detailed introduction of the mathematics of topology and concepts of machine learning algorithms. This provides an understanding for the central role which machine intelligence software is now playing in the emergence of the "learning healthcare system" and success in the new world of value-based healthcare delivery.

Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing

Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing Book
Author : Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Publisher : CRC Press
Release : 2020-12-23
ISBN : 1000337138
Language : En, Es, Fr & De

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Book Description :

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

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare Book
Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Release : 2020-06-21
ISBN : 0128184396
Language : En, Es, Fr & De

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Book Description :

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

Advancement of Artificial Intelligence in Healthcare Engineering

Advancement of Artificial Intelligence in Healthcare Engineering Book
Author : Dilip Singh Sisodia,Ram Bilas Pachori,Lalit Garg
Publisher : Medical Information Science Reference
Release : 2020
ISBN : 9781799821205
Language : En, Es, Fr & De

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Book Description :

"This book explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in the design, implementation, and optimization of challenging healthcare engineering solutions"--

Machine Learning for Healthcare Analytics Projects

Machine Learning for Healthcare Analytics Projects Book
Author : Eduonix Learning Solutions
Publisher : Packt Publishing Ltd
Release : 2018-10-30
ISBN : 1789532523
Language : En, Es, Fr & De

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Book Description :

Create real-world machine learning solutions using NumPy, pandas, matplotlib, and scikit-learn Key Features Develop a range of healthcare analytics projects using real-world datasets Implement key machine learning algorithms using a range of libraries from the Python ecosystem Accomplish intermediate-to-complex tasks by building smart AI applications using neural network methodologies Book Description Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors (KNN) models. In the final chapters, you will create a deep neural network in Keras to predict the onset of diabetes in a huge dataset of patients. You will also learn how to predict heart diseases using neural networks. By the end of this book, you will have learned how to address long-standing challenges, provide specialized solutions for how to deal with them, and carry out a range of cognitive tasks in the healthcare domain. What you will learn Explore super imaging and natural language processing (NLP) to classify DNA sequencing Detect cancer based on the cell information provided to the SVM Apply supervised learning techniques to diagnose autism spectrum disorder (ASD) Implement a deep learning grid and deep neural networks for detecting diabetes Analyze data from blood pressure, heart rate, and cholesterol level tests using neural networks Use ML algorithms to detect autistic disorders Who this book is for Machine Learning for Healthcare Analytics Projects is for data scientists, machine learning engineers, and healthcare professionals who want to implement machine learning algorithms to build smart AI applications. Basic knowledge of Python or any programming language is expected to get the most from this book.

AI and Machine Learning for Healthcare

AI and Machine Learning for Healthcare Book
Author : Aileen Nielsen
Publisher : Unknown
Release : 2017
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

"Artificial intelligence (AI) and machine learning (ML) in healthcare comprise a rapidly expanding and very promising field. The marriage of technology and health has the potential to empower medical professionals and patients alike, while drastically cutting the cost of healthcare. Using a measured no-hype approach, this video will help technology entrepreneurs, product managers, and health care executives understand what can be done with AI and ML in healthcare today and what concepts are most crucial to producing valuable applications in the near future."--Resource description page.

Big Data and Artificial Intelligence for Healthcare Applications

Big Data and Artificial Intelligence for Healthcare Applications Book
Author : Ankur Saxena,Nicolas Brault,Shazia Rashid
Publisher : Unknown
Release : 2021
ISBN : 9780367554958
Language : En, Es, Fr & De

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Book Description :

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. The book covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. This book will be useful for researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare Book
Author : Tom Lawry
Publisher : Himss Publishing
Release : 2020
ISBN : 9780367333713
Language : En, Es, Fr & De

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Book Description :

We are in the early stages of the next big platform shift in healthcare computing. Fueled by Artificial Intelligence (AI) and the cloud, AI is already transforming the way health and medical services are provided. As the industry transitions from static digital repositories to intelligent systems there will be winners and losers in the race to innovate and automate the provision of services. Critical to success will be the role leaders play in shaping the use of AI to be less "artificial" and more "intelligent" in support of improving processes to deliver care and keep people healthy and productive across all care settings. This book defines key technical, process, people and ethical issues that will need to be understood and addressed in planning and executing an effective AI plan. It provides clinical and business leaders with a framework for successfully moving organizations from the aspiration to execution phase of intelligent systems to improve clinical, operational and financial performance. Written for clinical and business leaders in health, this book defines Artificial Intelligence and its role in driving digital transformation to improve clinical, operational and financial outcomes of provider, payer and public health organizations worldwide. It provides readers with an in-depth (but non-technical) look at the technology "building blocks" of AI (e.g. machine learning, cognitive services, bots) with real-world use cases cited along the way to illustrate the power of AI in healthcare settings. This book defines a practical planning framework empowering clinical, business and IT leaders to understand AI and create an organizational plan to implement intelligent solutions that increase the effectiveness of every worker in achieving the goals and objectives of health and medical organizations.

Artificial Intelligence and Machine Learning for Business

Artificial Intelligence and Machine Learning for Business Book
Author : John Medicine
Publisher : Unknown
Release : 2021-02-03
ISBN : 9781914053450
Language : En, Es, Fr & De

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Book Description :

*55% OFF for Bookstores! Discounted Retail Price NOW at $11.69 instead of $25.99* The ultimate guide on Artificial Intelligence and Machine Learning, and how to apply it to the business and marketing, to be ahead from competitors. Your customers Will Never Stop to Use this Awesome Guide! Artificial intelligence technology has become so common that many people do not realize that AI is already a part of their lives. Businesses use AI in many realms, including predictive analytics, product pricing, and marketing. In healthcare, artificial intelligence can be used in medical image analysis, language processing in dictation, and automated healthcare services. Because of machine learning capabilities in AI, any data that artificial intelligence is provided with can be used to learn and to make new, unexpected predictions and recommendations. In this book, the reader will understand not only how AI works, but will also learn how machine learning is revolutionizing the industry. Although artificial intelligence can be complex, AI technology does not have to be a daunting subject. Understanding artificial intelligence requires a basic understanding of how machines can be programmed to think like humans. It is no surprise that AI is revolutionizing most areas of industry. Big tech companies have been on the forefront of AI because of their large amounts of data and their brain power in the form of machine learning teams, but anyone can learn how to use artificial intelligence to accomplish a basic business goal. Artificial intelligence technology has progressed so fast that many business leaders find themselves faced with the task of integrating all this new tech into how they do business. This can be a challenge for leaders and others whose core business function is not directly related to artificial intelligence or computer science. Artificial intelligence can be simply applied to business marketing strategies, social media engagement, and a host of other business functions. You will learn: - How Machine Learning works - AI Models and Networks - AI applied to complicated Tasks - How apply AI to your Marketing - How AI is changing Business - The secret of Big Tech companies and much more! Buy it NOW and let your customers get addicted to this amazing book!

Machine Learning for Healthcare Applications

Machine Learning for Healthcare Applications Book
Author : Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar
Publisher : John Wiley & Sons
Release : 2021-03-24
ISBN : 1119792606
Language : En, Es, Fr & De

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Book Description :

When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Medical Applications of Artificial Intelligence

Medical Applications of Artificial Intelligence Book
Author : Arvin Agah
Publisher : CRC Press
Release : 2013-11-06
ISBN : 143988434X
Language : En, Es, Fr & De

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Book Description :

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Applications of Artificial Intelligence reviews the research, focusing on state-of-the-art projects in the field. The book captures the breadth and depth of the medical applications of artificial intelligence, exploring new developments and persistent challenges.

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare Book
Author : Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
Publisher : Academic Press
Release : 2021-04-26
ISBN : 012823217X
Language : En, Es, Fr & De

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Book Description :

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

Deep Learning for Precision Diagnosis Surgery

Deep Learning for Precision Diagnosis   Surgery Book
Author : Vivek S. Jagadale
Publisher : Notion Press
Release : 2020-04-15
ISBN : 1648056989
Language : En, Es, Fr & De

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Book Description :

Artificial intelligence, smart applications, and virtual assistants are now revolutionizing every area of our lives, including healthcare delivery. This book introduces readers to the latest technological advances in the emerging field of augmented clinical care, machine learning for early diagnosis, and artificial intelligence-assisted precision surgery with orthopedics as a leading example. The applications of these techniques in orthopedic interventions offer many potential benefits, e.g., early diagnosis of elusive complications, precise templating and planning of surgery, systematic execution of the original plan with maximum accuracy, facilitating minimally invasive surgery and improving outcomes. This book is a valuable resource for all healthcare researchers, AI-based software developers and clinicians, on what is needed and what to expect to excel in the future of high-quality patient care. It also outlines why physicians must play a pivotal role in the development of these AI-based applications that will plainly define the future of personalized and cost-effective healthcare delivery for maximum patient safety and satisfaction. May the miracle you need be just around the corner.

AI and Medicine

AI and Medicine Book
Author : Michael Alan Barlow
Publisher : Unknown
Release : 2016
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download AI and Medicine book written by Michael Alan Barlow, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Data Pulse

Data Pulse Book
Author : Matthew Marcetich
Publisher : Unknown
Release : 2020-04-06
ISBN : 9781641375382
Language : En, Es, Fr & De

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Book Description :

For many of us, machine learning and artificial intelligence (AI) are abstract terms that have become popularized for their roles in automation and robotics. In healthcare, uses of AI emerged several decades ago and have significantly expanded to the present day. Data Pulse presents a current snapshot of uses of AI in healthcare, including essential opportunities and challenges. The discussion explores its impact at many levels of the healthcare system, from researchers and entrepreneurs to physicians and patients. With easily understood language, Marcetich defines common terms of AI and shows us how various AI tools are influencing research, clinical, and administrative areas of healthcare. The reader will learn how current discoveries build on the decades of previous work in biology, robotics, and computer science, along with the unforeseen ethical and legal challenges they have provoked. Data Pulse is a story of important partnerships and strategies that are reshaping modern healthcare through AI. It will inform our view of the past, present, and rapidly evolving future of AI in healthcare.