Download or read book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning written by Rani, Geeta and published by IGI Global. This book was released on 2020-10-16 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Download or read book Deep Learning Applications for Cyber Physical Systems written by Mundada, Monica R. and published by IGI Global. This book was released on 2021-12-17 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.

Download or read book Communities in Action written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-04-27 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the United States, some populations suffer from far greater disparities in health than others. Those disparities are caused not only by fundamental differences in health status across segments of the population, but also because of inequities in factors that impact health status, so-called determinants of health. Only part of an individual's health status depends on his or her behavior and choice; community-wide problems like poverty, unemployment, poor education, inadequate housing, poor public transportation, interpersonal violence, and decaying neighborhoods also contribute to health inequities, as well as the historic and ongoing interplay of structures, policies, and norms that shape lives. When these factors are not optimal in a community, it does not mean they are intractable: such inequities can be mitigated by social policies that can shape health in powerful ways. Communities in Action: Pathways to Health Equity seeks to delineate the causes of and the solutions to health inequities in the United States. This report focuses on what communities can do to promote health equity, what actions are needed by the many and varied stakeholders that are part of communities or support them, as well as the root causes and structural barriers that need to be overcome.

Download or read book Artificial Intelligence for COVID 19 written by Diego Oliva and published by Springer Nature. This book was released on 2021-07-19 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.

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

Download or read book Quality Assurance in the Era of Individualized Medicine written by Moumtzoglou, Anastasius S. and published by IGI Global. This book was released on 2019-11-29 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a significant deficiency among contemporary medicine practices reflected by experts making medical decisions for a large proportion of the population for which no or minimal data exists. Fortunately, our capacity to procure and apply such information is rapidly rising. As medicine becomes more individualized, the implementation of health IT and data interoperability become essential components to delivering quality healthcare. Quality Assurance in the Era of Individualized Medicine is a collection of innovative research on the methods and utilization of digital readouts to fashion an individualized therapy instead of a mass-population-directed strategy. While highlighting topics including assistive technologies, patient management, and clinical practices, this book is ideally designed for health professionals, doctors, nurses, hospital management, medical administrators, IT specialists, data scientists, researchers, academicians, and students.

Download or read book Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics written by Abhishek Kumar and published by CRC Press. This book was released on 2022-03-09 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.

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.

Download or read book AI for Health Equity and Fairness written by Arash Shaban-Nejad and published by Springer Nature. This book was released on with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Methods in Comparative Effectiveness Research written by Constantine Gatsonis and published by CRC Press. This book was released on 2017-02-24 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care (IOM 2009). CER is conducted to develop evidence that will aid patients, clinicians, purchasers, and health policy makers in making informed decisions at both the individual and population levels. CER encompasses a very broad range of types of studies—experimental, observational, prospective, retrospective, and research synthesis. This volume covers the main areas of quantitative methodology for the design and analysis of CER studies. The volume has four major sections—causal inference; clinical trials; research synthesis; and specialized topics. The audience includes CER methodologists, quantitative-trained researchers interested in CER, and graduate students in statistics, epidemiology, and health services and outcomes research. The book assumes a masters-level course in regression analysis and familiarity with clinical research.

Download or read book Targeted Learning written by Mark J. van der Laan and published by Springer Science & Business Media. This book was released on 2011-06-17 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the target parameter representing the scientific question of interest. This book is aimed at both statisticians and applied researchers interested in causal inference and general effect estimation for observational and experimental data. Part I is an accessible introduction to super learning and the targeted maximum likelihood estimator, including related concepts necessary to understand and apply these methods. Parts II-IX handle complex data structures and topics applied researchers will immediately recognize from their own research, including time-to-event outcomes, direct and indirect effects, positivity violations, case-control studies, censored data, longitudinal data, and genomic studies.

Download or read book Applications of Deep Learning and Big IoT on Personalized Healthcare Services written by Wason, Ritika and published by IGI Global. This book was released on 2020-02-07 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes. Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.

Download or read book Deep Learning Applications in Medical Imaging written by Saxena, Sanjay and published by IGI Global. This book was released on 2020-10-16 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

Download or read book Integrating AI in IoT Analytics on the Cloud for Healthcare Applications written by Jeya Mala, D. and published by IGI Global. This book was released on 2022-01-07 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Internet of things (IoT) applications employed for healthcare generate a huge amount of data that needs to be analyzed to produce the expected reports. To accomplish this task, a cloud-based analytical solution is ideal in order to generate faster reports in comparison to the traditional way. Given the current state of the world in which every day IoT devices are developed to provide healthcare solutions, it is essential to consider the mechanisms used to collect and analyze the data to provide thorough reports. Integrating AI in IoT Analytics on the Cloud for Healthcare Applications applies artificial intelligence (AI) in edge analytics for healthcare applications, analyzes the impact of tools and techniques in edge analytics for healthcare, and discusses security solutions for edge analytics in healthcare IoT. Covering topics such as data analytics and next generation healthcare systems, it is ideal for researchers, academicians, technologists, IT specialists, data scientists, healthcare industries, IoT developers, data security analysts, educators, and students.

Download or read book Machine Learning Algorithms Using Scikit and TensorFlow Environments written by Baby Maruthi, Puvvadi and published by IGI Global. This book was released on 2023-12-18 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.

Download or read book The Future of Nursing 2020 2030 written by National Academies of Sciences Engineering and Medicine and published by . This book was released on 2021-09-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The decade ahead will test the nation's nearly 4 million nurses in new and complex ways. Nurses live and work at the intersection of health, education, and communities. Nurses work in a wide array of settings and practice at a range of professional levels. They are often the first and most frequent line of contact with people of all backgrounds and experiences seeking care and they represent the largest of the health care professions. A nation cannot fully thrive until everyone - no matter who they are, where they live, or how much money they make - can live their healthiest possible life, and helping people live their healthiest life is and has always been the essential role of nurses. Nurses have a critical role to play in achieving the goal of health equity, but they need robust education, supportive work environments, and autonomy. Accordingly, at the request of the Robert Wood Johnson Foundation, on behalf of the National Academy of Medicine, an ad hoc committee under the auspices of the National Academies of Sciences, Engineering, and Medicine conducted a study aimed at envisioning and charting a path forward for the nursing profession to help reduce inequities in people's ability to achieve their full health potential. The ultimate goal is the achievement of health equity in the United States built on strengthened nursing capacity and expertise. By leveraging these attributes, nursing will help to create and contribute comprehensively to equitable public health and health care systems that are designed to work for everyone. The Future of Nursing 2020-2030: Charting a Path to Achieve Health Equity explores how nurses can work to reduce health disparities and promote equity, while keeping costs at bay, utilizing technology, and maintaining patient and family-focused care into 2030. This work builds on the foundation set out by The Future of Nursing: Leading Change, Advancing Health (2011) report.

Download or read book Machine Learning in Cardiovascular Medicine written by Subhi J. Al'Aref, M.D. and published by Academic Press. This book was released on 2020-12-11 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach