Machine Learning In Healthcare And Security

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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

Machine Learning in Healthcare and Security

Author : Prashant Pranav
Publisher : CRC Press
ISBN 13 : 1003825885
Total Pages : 225 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Machine Learning in Healthcare and Security by : Prashant Pranav

Download or read book Machine Learning in Healthcare and Security written by Prashant Pranav and published by CRC Press. This book was released on 2024-01-19 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a blend of different areas of machine learning and recent advances in the area. From the use of ML in healthcare to security, this book encompasses several areas related to ML while keeping a check on traditional ML algorithms. Machine Learning in Healthcare and Security: Advances, Obstacles, and Solutions describes the predictive analysis and forecasting techniques in different emerging and classical areas using the approaches of ML and AI. It discusses the application of ML and AI in medical diagnostic systems and deals with the security prevention aspects of ML and how it can be used to tackle various emerging security issues. This book also focuses on NLP and understanding the techniques, obstacles, and possible solutions. This is a valuable reference resource for researchers and postgraduate students in healthcare systems engineering, computer science, cyber-security, information technology, and applied mathematics.

Machine Learning with Health Care Perspective

Author : Vishal Jain
Publisher : Springer Nature
ISBN 13 : 3030408507
Total Pages : 418 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning with Health Care Perspective by : Vishal Jain

Download or read book Machine Learning with Health Care Perspective written by Vishal Jain and published by Springer Nature. This book was released on 2020-03-09 with total page 418 pages. Available in PDF, EPUB and Kindle. Book 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.

Internet of Healthcare Things

Author : Kavita Sharma
Publisher : John Wiley & Sons
ISBN 13 : 1119791766
Total Pages : 308 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Internet of Healthcare Things by : Kavita Sharma

Download or read book Internet of Healthcare Things written by Kavita Sharma and published by John Wiley & Sons. This book was released on 2022-03-09 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTERNET OF HEALTHCARE THINGS The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making. The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book. Audience Researchers and industry engineers in computer science, artificial intelligence, healthcare sector, IT professionals, network administrators, cybersecurity experts.

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.

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

Handbook of Security and Privacy of AI-Enabled Healthcare Systems and Internet of Medical Things

Author : Agbotiname Lucky Imoize
Publisher : CRC Press
ISBN 13 : 1000963268
Total Pages : 536 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Handbook of Security and Privacy of AI-Enabled Healthcare Systems and Internet of Medical Things by : Agbotiname Lucky Imoize

Download or read book Handbook of Security and Privacy of AI-Enabled Healthcare Systems and Internet of Medical Things written by Agbotiname Lucky Imoize and published by CRC Press. This book was released on 2023-10-25 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions. This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others. .

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.

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

Author : Om Prakash Jena
Publisher : CRC Press
ISBN 13 : 1000486796
Total Pages : 397 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems by : Om Prakash Jena

Download or read book Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems written by Om Prakash Jena and published by CRC Press. This book was released on 2022-05-18 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications. FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analytics This book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.

Artificial Intelligence in Healthcare and Medicine

Author : Kayvan Najarian
Publisher : CRC Press
ISBN 13 : 1000565815
Total Pages : 300 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Artificial Intelligence in Healthcare and Medicine by : Kayvan Najarian

Download or read book Artificial Intelligence in Healthcare and Medicine written by Kayvan Najarian and published by CRC Press. This book was released on 2022-04-06 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.

Machine Learning and Analytics in Healthcare Systems

Author : Himani Bansal
Publisher : CRC Press
ISBN 13 : 1000406199
Total Pages : 275 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning and Analytics in Healthcare Systems by : Himani Bansal

Download or read book Machine Learning and Analytics in Healthcare Systems written by Himani Bansal and published by CRC Press. This book was released on 2021-06-30 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy. The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.

Machine Learning and Cognitive Science Applications in Cyber Security

Author : Khan, Muhammad Salman
Publisher : IGI Global
ISBN 13 : 1522581014
Total Pages : 321 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Machine Learning and Cognitive Science Applications in Cyber Security by : Khan, Muhammad Salman

Download or read book Machine Learning and Cognitive Science Applications in Cyber Security written by Khan, Muhammad Salman and published by IGI Global. This book was released on 2019-05-15 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a variety of sources have been exposed to possible corruption and hacking. Machine learning, artificial intelligence, predictive analytics, and similar disciplines of cognitive science applications have been found to have significant applications in the domain of cyber security. Machine Learning and Cognitive Science Applications in Cyber Security examines different applications of cognition that can be used to detect threats and analyze data to capture malware. Highlighting such topics as anomaly detection, intelligent platforms, and triangle scheme, this publication is designed for IT specialists, computer engineers, researchers, academicians, and industry professionals interested in the impact of machine learning in cyber security and the methodologies that can help improve the performance and reliability of machine learning applications.

Blockchain and Machine Learning for e-Healthcare Systems

Author : Balusamy Balamurugan
Publisher : Institution of Engineering and Technology
ISBN 13 : 1839531142
Total Pages : 480 pages
Book Rating : 4.8/5 (395 download)

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Book Synopsis Blockchain and Machine Learning for e-Healthcare Systems by : Balusamy Balamurugan

Download or read book Blockchain and Machine Learning for e-Healthcare Systems written by Balusamy Balamurugan and published by Institution of Engineering and Technology. This book was released on 2020-11-13 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blockchain and machine learning technologies can mitigate healthcare issues such as slow access to medical data, poor system interoperability, lack of patient agency, and data quality and quantity for medical research. Blockchain technology facilitates and secures the storage of information in such a way that doctors can see a patient's entire medical history, but researchers see only statistical data instead of any personal information. Machine learning can make use of this data to notice patterns and give accurate predictions, providing more support for the patients and also in research related fields where there is a need for accurate data to predict credible results.

Smart Healthcare Systems

Author : Adwitiya Sinha
Publisher : CRC Press
ISBN 13 : 0429670281
Total Pages : 332 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Smart Healthcare Systems by : Adwitiya Sinha

Download or read book Smart Healthcare Systems written by Adwitiya Sinha and published by CRC Press. This book was released on 2019-07-24 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.

Artificial Intelligence Technology in Healthcare

Author : Neha Sharma (Computer scientist)
Publisher :
ISBN 13 : 9781003377818
Total Pages : 0 pages
Book Rating : 4.3/5 (778 download)

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Book Synopsis Artificial Intelligence Technology in Healthcare by : Neha Sharma (Computer scientist)

Download or read book Artificial Intelligence Technology in Healthcare written by Neha Sharma (Computer scientist) and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focusses on current issues with the patient's privacy and data security including data breaches in healthcare organizations, unauthorized access to patient's information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to develop AI-based security mechanisms which can gather or share data across several healthcare applications securely and privately. The book combines multiple technologies (i.e., IoT, Federated Computing, and AI) for managing and securing smart healthcare systems and includes state-of-the-art machine learning, deep learning techniques for predictive analysis, fog and edge computing based real-time health monitoring. It covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches and focusses on latest research on privacy, security, and threat detection on COVID19 through IoT. It also illustrates initiatives for research in smart computing for advanced healthcare management systems. This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering"--

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

Author : Om Prakash Jena
Publisher : CRC Press
ISBN 13 : 1000486826
Total Pages : 321 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems by : Om Prakash Jena

Download or read book Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems written by Om Prakash Jena and published by CRC Press. This book was released on 2022-05-18 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications. FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analytics This book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.

Introduction to Deep Learning for Healthcare

Author : Cao Xiao
Publisher : Springer Nature
ISBN 13 : 3030821846
Total Pages : 236 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Introduction to Deep Learning for Healthcare by : Cao Xiao

Download or read book Introduction to Deep Learning for Healthcare written by Cao Xiao and published by Springer Nature. This book was released on 2021-11-11 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents deep learning models and their healthcare applications. It focuses on rich health data and deep learning models that can effectively model health data. Healthcare data: Among all healthcare technologies, electronic health records (EHRs) had vast adoption and a significant impact on healthcare delivery in recent years. One crucial benefit of EHRs is to capture all the patient encounters with rich multi-modality data. Healthcare data include both structured and unstructured information. Structured data include various medical codes for diagnoses and procedures, lab results, and medication information. Unstructured data contain 1) clinical notes as text, 2) medical imaging data such as X-rays, echocardiogram, and magnetic resonance imaging (MRI), and 3) time-series data such as the electrocardiogram (ECG) and electroencephalogram (EEG). Beyond the data collected during clinical visits, patient self-generated/reported data start to grow thanks to wearable sensors’ increasing use. The authors present deep learning case studies on all data described. Deep learning models: Neural network models are a class of machine learning methods with a long history. Deep learning models are neural networks of many layers, which can extract multiple levels of features from raw data. Deep learning applied to healthcare is a natural and promising direction with many initial successes. The authors cover deep neural networks, convolutional neural networks, recurrent neural networks, embedding methods, autoencoders, attention models, graph neural networks, memory networks, and generative models. It’s presented with concrete healthcare case studies such as clinical predictive modeling, readmission prediction, phenotyping, x-ray classification, ECG diagnosis, sleep monitoring, automatic diagnosis coding from clinical notes, automatic deidentification, medication recommendation, drug discovery (drug property prediction and molecule generation), and clinical trial matching. This textbook targets graduate-level students focused on deep learning methods and their healthcare applications. It can be used for the concepts of deep learning and its applications as well. Researchers working in this field will also find this book to be extremely useful and valuable for their research.