Artificial Intelligence And Big Data For Value Based Care
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Artificial Intelligence And Big Data Analytics For Smart Healthcare
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Author : Miltiadis Lytras
language : en
Publisher: Academic Press
Release Date : 2021-10-22
Artificial Intelligence And Big Data Analytics For Smart Healthcare written by Miltiadis Lytras and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Medical categories.
Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers
Artificial Intelligence And Big Data For Value Based Care
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Author : Md. Mohaimenul Islam
language : en
Publisher: Frontiers Media SA
Release Date : 2023-03-01
Artificial Intelligence And Big Data For Value Based Care written by Md. Mohaimenul Islam and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Medical categories.
Big Data Analytics And Intelligence
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Author : Poonam Tanwar
language : en
Publisher: Emerald Group Publishing
Release Date : 2020-09-30
Big Data Analytics And Intelligence written by Poonam Tanwar and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-30 with Business & Economics categories.
Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Big Data Analytics And Artificial Intelligence In The Healthcare Industry
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Author : Machado, José
language : en
Publisher: IGI Global
Release Date : 2022-04-29
Big Data Analytics And Artificial Intelligence In The Healthcare Industry written by Machado, José and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-29 with Computers categories.
Developing new approaches and reliable enabling technologies in the healthcare industry is needed to enhance our overall quality of life and lead to a healthier, innovative, and secure society. Further study is required to ensure these current technologies, such as big data analytics and artificial intelligence, are utilized to their utmost potential and are appropriately applied to advance society. Big Data Analytics and Artificial Intelligence in the Healthcare Industry discusses technologies and emerging topics regarding reliable and innovative solutions applied to the healthcare industry and considers various applications, challenges, and issues of big data and artificial intelligence for enhancing our quality of life. Covering a range of topics such as electronic health records, machine learning, and e-health, this reference work is ideal for healthcare professionals, computer scientists, data analysts, researchers, practitioners, scholars, academicians, instructors, and students.
Analytics In Healthcare
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Author : Christo El Morr
language : en
Publisher: Springer
Release Date : 2019-01-21
Analytics In Healthcare written by Christo El Morr and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-21 with Medical categories.
This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records, electronic patient record, clinical findings, diagnosis, prescription drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use it to make well-informed decisions can be a challenge for managers and health care professionals. A new generation of applications, sometimes referred to as end-user analytics or self-serve analytics, are specifically designed for non-technical users such as managers and business professionals. The ability to use these increasingly accessible tools with the abundant data requires a basic understanding of the core concepts of data, analytics, and interpretation of outcomes. This book is a resource for such individuals to demystify and learn the basics of data management and analytics for healthcare, while also looking towards future directions in the field.
Instructional Course Lectures Volume 73
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Author : Ronald A. Navarro
language : en
Publisher: Lippincott Williams & Wilkins
Release Date : 2023-12-28
Instructional Course Lectures Volume 73 written by Ronald A. Navarro and has been published by Lippincott Williams & Wilkins this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-28 with Medical categories.
Developed in partnership with the American Academy of Orthopaedic Surgeons (AAOS) and edited by Ronald A. Navarro, MD, FAAOS, FAOA (editor) and Carolyn M. Hettrich, MD, MPH, FAAOS (assistant editor), Instructional Course Lectures, Volume 73 offers current, clinically relevant information across a broad spectrum of orthopaedic topics. These lectures were written by the orthopaedic surgeons who presented at the 2023 AAOS Annual Meeting. This all-new volume covers topics such as: • From Platelet-Rich Plasma to Mesenchymal Stem Cells: Cartilage Regeneration With Orthobiologics • Patient Reported Outcome Measures – How to Get the Most Out of Them and Mitigate Health Care Disparities • Leveraging Artificial Intelligence and Digital Health to Address Health-Related Social Needs and Optimize Risk-Based Value in Orthopaedic Surgery • Peri-articular Injection and Peripheral Nerve Blocks With Standard Agents • Management of Acute Diabetic Ankle Fractures • And many more
An Integrative Paradigm For Mental Health Care
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Author : James H. Lake
language : en
Publisher: Springer
Release Date : 2019-05-28
An Integrative Paradigm For Mental Health Care written by James H. Lake and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-28 with Psychology categories.
This crucial volume provides a concise overview of the conceptual foundations and clinical methods underlying the rapidly emerging subspecialty of integrative mental healthcare. It discusses methods for guiding practitioners to individualized integrative strategies that address unique symptoms and circumstances for each patient and includes practical clinical techniques for developing interventions addressed at wellness, prevention, and treatment. Included among the overview: Meeting the challenges of mental illness through integrative mental health care. Evolving paradigms and their impact on mental health care Models of consciousness: How they shape understandings of normal mental functioning and mental illness Foundations of methodology in integrative mental health care Treatment planning in integrative mental health care The future of mental health care A New Paradigm for Integrative Mental Healthcare is relevant and timely for the increasing numbers of patients seeking integrative and alternative care for depressed mood, anxiety, ADHD, bipolar disorder, schizophrenia, and other mental health problems such as fatigue and chronic pain. “Patients are crying out for a more integrative approach, and this exemplary book provides the template for achieving such a vision.” -Jerome Sarris, MHSc, PhD, ND “For most conventionally trained clinicians the challenge is not “does CAM work?” but “how do I integrate CAM into my clinical practice?” Lake’s comprehensive approach answers this central question, enabling the clinician to plan truly integrative and effective care for the mind and body.” -Leslie Korn, PhD, MPH
Deep Learning Machine Learning And Iot In Biomedical And Health Informatics
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Author : Sujata Dash
language : en
Publisher: CRC Press
Release Date : 2022-02-10
Deep Learning Machine Learning And Iot In Biomedical And Health Informatics written by Sujata Dash and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-10 with Computers categories.
Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others. • Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications • Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches • Discusses various techniques of IoT systems for healthcare data analytics • Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics • Focuses more on the application of algorithms in various real life biomedical and engineering problems
Optimized Predictive Models In Health Care Using Machine Learning
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Author : Sandeep Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2024-03-12
Optimized Predictive Models In Health Care Using Machine Learning written by Sandeep Kumar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-12 with Computers categories.
OPTIMIZED PREDICTIVE MODELS IN HEALTH CARE USING MACHINE LEARNING This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using machine learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications. The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs. Other essential features of the book include: provides detailed guidance on data collection and preprocessing, emphasizing the importance of collecting accurate and reliable data; explains how to transform raw data into meaningful features that can be used to improve the accuracy of predictive models; gives a detailed overview of machine learning algorithms for predictive modeling in healthcare, discussing the pros and cons of different algorithms and how to choose the best one for a specific application; emphasizes validating and evaluating predictive models; provides a comprehensive overview of validation and evaluation techniques and how to evaluate the performance of predictive models using a range of metrics; discusses the challenges and limitations of predictive modeling in healthcare; highlights the ethical and legal considerations that must be considered when developing predictive models and the potential biases that can arise in those models. Audience The book will be read by a wide range of professionals who are involved in healthcare, data science, and machine learning.