Artificial Intelligence and Machine Learning in Healthcare Book

Artificial Intelligence and Machine Learning in Healthcare


  • Author : Ankur Saxena
  • Publisher : Springer Nature
  • Release Date : 2021-05-06
  • Genre: Science
  • Pages : 228
  • ISBN 10 : 9789811608117

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Artificial Intelligence and Machine Learning in Healthcare 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.

Machine Learning and AI for Healthcare Book
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Machine Learning and AI for Healthcare


  • Author : Arjun Panesar
  • Publisher : Apress
  • Release Date : 2019-02-04
  • Genre: Computers
  • Pages : 390
  • ISBN 10 : 9781484237991

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Machine Learning and AI for Healthcare 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.

Deep Learning in Healthcare Book

Deep Learning in Healthcare


  • Author : Yen-Wei Chen
  • Publisher : Springer Nature
  • Release Date : 2019-11-18
  • Genre: Technology & Engineering
  • Pages : 218
  • ISBN 10 : 9783030326067

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Deep Learning in Healthcare 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.

Artificial Intelligence and Machine Learning in Public Healthcare Book

Artificial Intelligence and Machine Learning in Public Healthcare


  • Author : KC Santosh
  • Publisher : Springer
  • Release Date : 2021-11-27
  • Genre: Technology & Engineering
  • Pages : 74
  • ISBN 10 : 9811667675

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Artificial Intelligence and Machine Learning in Public Healthcare 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 in Healthcare Book

Artificial Intelligence in Healthcare


  • Author : Adam Bohr
  • Publisher : Academic Press
  • Release Date : 2020-06-21
  • Genre: Computers
  • Pages : 378
  • ISBN 10 : 9780128184394

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Artificial Intelligence in Healthcare 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

Data Analytics in Bioinformatics Book

Data Analytics in Bioinformatics


  • Author : Rabinarayan Satpathy
  • Publisher : John Wiley & Sons
  • Release Date : 2021-01-20
  • Genre: Computers
  • Pages : 544
  • ISBN 10 : 9781119785606

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Data Analytics in Bioinformatics Excerpt :

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Artificial Intelligence and Machine Learning in Healthcare Book

Artificial Intelligence and Machine Learning in Healthcare


  • Author : Arman Kilic
  • Publisher : Academic Press
  • Release Date : 2022-06-01
  • Genre: Business & Economics
  • Pages : 300
  • ISBN 10 : 9780128225196

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Artificial Intelligence and Machine Learning in Healthcare Excerpt :

Artificial Intelligence and Machine Learning in Healthcare discusses the potential of groundbreaking technologies on the delivery of care. A lot have been said about how artificial intelligence and machine learning can improve healthcare, however there are still many doubts and concerns among health professionals, all of which are addressed in this book. Sections cover History and Basic Overview of AI and ML, with differentiation of supervised, unsupervised and deep learning, Applications of AI and ML in Healthcare, The Future of Healthcare with AI, Challenges to Adopting AI in Healthcare, and ethics and legal processes for implementation. This book is a valuable resource for bioinformaticians, clinicians, graduate students and several members of biomedical field who needs to get up to speed on the revolutionary role of AI and Machine Learning in healthcare. Provides an overview of AI and ML to the medical practitioner who may not be well versed in these fields Encompasses a thorough review of what has been accomplished and demonstrated recently in the fields of AI and ML in healthcare Discusses the future of AI and ML in healthcare, with a review of possible wearable technology and software and how they may be used for medical care

Big Data and Artificial Intelligence for Healthcare Applications Book

Big Data and Artificial Intelligence for Healthcare Applications


  • Author : Ankur Saxena
  • Publisher : CRC Press
  • Release Date : 2021-06-15
  • Genre: Computers
  • Pages : 286
  • ISBN 10 : 9781000387315

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Big Data and Artificial Intelligence for Healthcare Applications Excerpt :

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. "Big Data and Artificial Intelligence for Healthcare Applications" 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. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

Artificial Intelligence Book

Artificial Intelligence


  • Author : Sandeep Reddy
  • Publisher : CRC Press
  • Release Date : 2020-12-02
  • Genre: Business & Economics
  • Pages : 287
  • ISBN 10 : 9781000216868

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Artificial Intelligence 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.

Machine Learning with Health Care Perspective Book

Machine Learning with Health Care Perspective


  • Author : Vishal Jain
  • Publisher : Springer Nature
  • Release Date : 2020-03-09
  • Genre: Technology & Engineering
  • Pages : 415
  • ISBN 10 : 9783030408503

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Machine Learning with Health Care Perspective Excerpt :

This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.

Machine Learning and the Internet of Medical Things in Healthcare Book

Machine Learning and the Internet of Medical Things in Healthcare


  • Author : Krishna Kant Singh
  • Publisher : Academic Press
  • Release Date : 2021-04-26
  • Genre: Science
  • Pages : 290
  • ISBN 10 : 9780128232170

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Machine Learning and the Internet of Medical Things in Healthcare 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 Healthcare Book

Artificial Intelligence in Healthcare


  • Author : Parag Mahajan
  • Publisher : Medmantra, LLC
  • Release Date : 2021-02
  • Genre: Uncategoriezed
  • Pages : 628
  • ISBN 10 : 1954612028

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Artificial Intelligence in Healthcare 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.

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

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


  • Author : Rohit Raja
  • Publisher : CRC Press
  • Release Date : 2020-12-22
  • Genre: Technology & Engineering
  • Pages : 196
  • ISBN 10 : 9781000337075

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

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

Machine Learning in Healthcare Book

Machine Learning in Healthcare


  • Author : Bikesh Kumar Singh
  • Publisher : Unknown
  • Release Date : 2022
  • Genre: Uncategoriezed
  • Pages : null
  • ISBN 10 : 0367564432

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Machine Learning in Healthcare Excerpt :

"Machine Learning in Healthcare discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. It covers fundamental concepts including mathematical requisites and traditional machine-learning framework followed by advanced machine-learning methods and their applications in medical fields"--

Demystifying Big Data and Machine Learning for Healthcare Book

Demystifying Big Data and Machine Learning for Healthcare


  • Author : Prashant Natarajan
  • Publisher : CRC Press
  • Release Date : 2017-02-15
  • Genre: Medical
  • Pages : 233
  • ISBN 10 : 9781315389301

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Demystifying Big Data and Machine Learning for Healthcare Excerpt :

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.