Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease

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Publisher : IGI Global
ISBN 13 : 1799871908
Total Pages : 241 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease by : Roy, Manikant

Download or read book Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease written by Roy, Manikant and published by IGI Global. This book was released on 2021-06-25 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.

AI and Machine Learning Paradigms for Health Monitoring System

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Publisher : Springer Nature
ISBN 13 : 9813344121
Total Pages : 513 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis AI and Machine Learning Paradigms for Health Monitoring System by : Hasmat Malik

Download or read book AI and Machine Learning Paradigms for Health Monitoring System written by Hasmat Malik and published by Springer Nature. This book was released on 2021-02-14 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.

Big Data Analytics and Intelligence

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Publisher : Emerald Group Publishing
ISBN 13 : 1839091010
Total Pages : 252 pages
Book Rating : 4.8/5 (39 download)

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Book Synopsis Big Data Analytics and Intelligence by : Poonam Tanwar

Download or read book Big Data Analytics and Intelligence written by Poonam Tanwar and published by Emerald Group Publishing. This book was released on 2020-09-30 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms

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Publisher : IGI Global
ISBN 13 : 1799883523
Total Pages : 296 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms by : Milutinovi?, Veljko

Download or read book Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms written by Milutinovi?, Veljko and published by IGI Global. This book was released on 2022-03-11 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

Disease Prediction using Machine Learning, Deep Learning and Data Analytics

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Publisher : Bentham Science Publishers
ISBN 13 : 9815179136
Total Pages : 196 pages
Book Rating : 4.8/5 (151 download)

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Book Synopsis Disease Prediction using Machine Learning, Deep Learning and Data Analytics by : Geeta Rani, Vijaypal Singh Dhaka, Pradeep Kumar Tiwari

Download or read book Disease Prediction using Machine Learning, Deep Learning and Data Analytics written by Geeta Rani, Vijaypal Singh Dhaka, Pradeep Kumar Tiwari and published by Bentham Science Publishers. This book was released on 2024-03-07 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive review of technologies and data in healthcare services. It features a compilation of 10 chapters that inform readers about the recent research and developments in this field. Each chapter focuses on a specific aspect of healthcare services, highlighting the potential impact of technology on enhancing practices and outcomes. The main features of the book include 1) referenced contributions from healthcare and data analytics experts, 2) a broad range of topics that cover healthcare services, and 3) demonstration of deep learning techniques for specific diseases. Key topics: - Federated learning in analysis of sensitive healthcare data while preserving privacy and security. - Artificial intelligence for 3-D bone image reconstruction. - Detection of disease severity and creating personalized treatment plans using machine learning and software tools - Case studies for disease detection methods for different disease and conditions, including dementia, asthma, eye diseases - Brain-computer interfaces - Data mining for standardized electronic health records - Data collection, management, and analysis in epidemiological research The book is a resource for learners and professionals in healthcare service training programs and health administration departments. Readership Learners and professionals in healthcare service training programs and health administration departments.

Big Data Analytics for Healthcare

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Publisher : Academic Press
ISBN 13 : 0323985165
Total Pages : 356 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Big Data Analytics for Healthcare by : Pantea Keikhosrokiani

Download or read book Big Data Analytics for Healthcare written by Pantea Keikhosrokiani and published by Academic Press. This book was released on 2022-05-19 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. Presents theories, methods and approaches in which data analytic techniques are used for medical data Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases Discusses social, behavioral, and medical fake news analytics for medical information systems

Machine Learning and Analytics in Healthcare Systems

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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: Bridges the gap between engineering and medicine in combining the design and problem solving skills of engineering with health sciences Explores real-world case studies in machine learning and healthcare analytics Presents a detailed exploration of applications of machine learning in healthcare systems Provides readers with how the industry avoids some of the consequences of old methods of data sharing strategies Offers readers multiple perspectives on a variety of disciplines

New Approaches to Data Analytics and Internet of Things Through Digital Twin

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Publisher : IGI Global
ISBN 13 : 1668457245
Total Pages : 326 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis New Approaches to Data Analytics and Internet of Things Through Digital Twin by : Karthikeyan, P.

Download or read book New Approaches to Data Analytics and Internet of Things Through Digital Twin written by Karthikeyan, P. and published by IGI Global. This book was released on 2022-09-30 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Reinventing Clinical Decision Support

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Publisher : Taylor & Francis
ISBN 13 : 1000055558
Total Pages : 164 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis Reinventing Clinical Decision Support by : Paul Cerrato

Download or read book Reinventing Clinical Decision Support written by Paul Cerrato and published by Taylor & Francis. This book was released on 2020-01-06 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it’s forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

Management for Digital Transformation

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Publisher : Springer Nature
ISBN 13 : 3031420608
Total Pages : 226 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Management for Digital Transformation by : Carolina Machado

Download or read book Management for Digital Transformation written by Carolina Machado and published by Springer Nature. This book was released on 2023-10-25 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive resource for managers, engineers, researchers, academics, and professionals from various fields seeking to grasp the complexities and opportunities presented by digital transformation. It goes beyond the superficial understanding of digitalization, delving into the intricacies of this transformative process and its profound impact on organizations. By exploring the latest developments and insights from around the world, readers will gain a deep understanding of how digital transformation influences not only technological aspects but also human resources, processes, relationships, and information management. With a critical lens, this book addresses the challenges and changes that arise in the context of digital transformation, empowering readers to effectively lead and manage these processes. From examining the role of technology transfer to discussing talent management, consumer vulnerabilities, generative AIs, and the evolving landscape of e-commerce and internet use, this book provides a rich tapestry of knowledge and practical recommendations. It also highlights the significance of collaboration, virtual teams, and intelligent tools in driving digitalization. Moreover, it explores innovative management practices and techniques for addressing mobile phone waste, utilizing scientometric, bibliometric, and visual analytic tools. Ultimately, this book equips readers with the necessary insights and strategies to navigate the digital transformation successfully and harness its potential to achieve organizational excellence in an increasingly dynamic world.

Artificial Intelligence in Healthcare

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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

Predictive Analytics of Psychological Disorders in Healthcare

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Publisher : Springer Nature
ISBN 13 : 9811917248
Total Pages : 310 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Predictive Analytics of Psychological Disorders in Healthcare by : Mamta Mittal

Download or read book Predictive Analytics of Psychological Disorders in Healthcare written by Mamta Mittal and published by Springer Nature. This book was released on 2022-05-20 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses an interdisciplinary field which combines two major domains: healthcare and data analytics. It presents research studies by experts helping to fight discontent, distress, anxiety and unrealized potential by using mathematical models, machine learning, artificial intelligence, etc. and take preventive measures beforehand. Psychological disorders and biological abnormalities are significantly related with the applications of cognitive illnesses which has increased significantly in contemporary years and needs rapid investigation. The research content of this book is helpful for psychological undergraduates, health workers and their trainees, therapists, medical psychologists, and nurses.

IoT, Machine Learning and Data Analytics for Smart Healthcare

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Publisher : CRC Press
ISBN 13 : 1003860664
Total Pages : 118 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis IoT, Machine Learning and Data Analytics for Smart Healthcare by : Mourade Azrour

Download or read book IoT, Machine Learning and Data Analytics for Smart Healthcare written by Mourade Azrour and published by CRC Press. This book was released on 2024-03-13 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system. This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues. This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students

Advances in Computing and Data Sciences

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Publisher : Springer Nature
ISBN 13 : 3031379403
Total Pages : 611 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Advances in Computing and Data Sciences by : Mayank Singh

Download or read book Advances in Computing and Data Sciences written by Mayank Singh and published by Springer Nature. This book was released on 2023-08-23 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Advances in Computing and Data Sciences, ICACDS 2023, held in Kolkata, India, during April 27–28, 2023. The 47 full papers included in this book were carefully reviewed and selected from 22 submissions. The papers focus on advances of next generation computing technologies in the areas of advanced computing and data sciences.

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

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Publisher : IGI Global
ISBN 13 : 1799827437
Total Pages : 586 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning by : Rani, Geeta

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.

Intelligent Techniques for Predictive Data Analytics

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Publisher : Wiley-IEEE Press
ISBN 13 : 9781394227969
Total Pages : 0 pages
Book Rating : 4.2/5 (279 download)

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Book Synopsis Intelligent Techniques for Predictive Data Analytics by : Neha Singh

Download or read book Intelligent Techniques for Predictive Data Analytics written by Neha Singh and published by Wiley-IEEE Press. This book was released on 2024-10-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive resource covering tools and techniques used for predictive analytics with practical applications across various industries Intelligent Techniques for Predictive Data Analytics provides an in-depth introduction of the tools and techniques used for predictive analytics, covering applications in cyber security, network security, data mining, and machine learning across various industries. Each chapter offers a brief introduction on the subject to make the text accessible regardless of background knowledge. Readers will gain a clear understanding of how to use data processing, classification, and analysis to support strategic decisions, such as by optimizing marketing strategies and customer relationship management and recommendation systems, improving general business operations, and predicting occurrence of chronic diseases for better patient management. Traditional data analytics uses dashboards to illustrate trends and outliers, but with large data sets, the process is labor-intensive and time-consuming. This book provides everything readers need to save time by performing deep, efficient analysis without human bias and time constraints. A section on current challenges in the field is also included. Intelligent Techniques for Predictive Data Analytics covers sample topics such as: ● Models to choose from in predictive modeling, including classification, clustering, forecast, outlier, and time series models ● Price forecasting, quality optimization, and insect and disease plant and monitoring in agriculture ● Fraud detection and prevention, credit scoring, financial planning, and customer analytics in banking ● Big data in smart grids, smart grid analytics, and predictive smart grid quality monitoring, maintenance, and load forecasting ● Management of uncertainty in predictive data analytics and probable future developments in the field Intelligent Techniques for Predictive Data Analytics is an essential resource on the subject for professionals and researchers working in data science or data management seeking to understand the different models of predictive analytics, along with graduate students studying data science courses and professionals and academics new to the field.

Green Computing and Predictive Analytics for Healthcare

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Publisher : CRC Press
ISBN 13 : 1000223949
Total Pages : 205 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Green Computing and Predictive Analytics for Healthcare by : Sourav Banerjee

Download or read book Green Computing and Predictive Analytics for Healthcare written by Sourav Banerjee and published by CRC Press. This book was released on 2020-12-10 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Green Computing and Predictive Analytics for Healthcare excavates the rudimentary concepts of Green Computing, Big Data and the Internet of Things along with the latest research development in the domain of healthcare. It also covers various applications and case studies in the field of computer science with state-of-the-art tools and technologies. The rapid growth of the population is a challenging issue in maintaining and monitoring various experiences of quality of service in healthcare. The coherent usage of these limited resources in connection with optimum energy consumption has been becoming more important. The major healthcare nodes are gradually becoming Internet of Things-enabled, and sensors, work data and the involvement of networking are creating smart campuses and smart houses. The book includes chapters on the Internet of Things and Big Data technologies. Features: Biomedical data monitoring under the Internet of Things Environment data sensing and analyzing Big data analytics and clustering Machine learning techniques for sudden cardiac death prediction Robust brain tissue segmentation Energy-efficient and green Internet of Things for healthcare applications Blockchain technology for the healthcare Internet of Things Advanced healthcare for domestic medical tourism system Edge computing for data analytics This book on Green Computing and Predictive Analytics for Healthcare aims to promote and facilitate the exchange of research knowledge and findings across different disciplines on the design and investigation of healthcare data analytics. It can also be used as a textbook for a master’s course in biomedical engineering. This book will also present new methods for medical data evaluation and the diagnosis of different diseases to improve quality-of-life in general and for better integration of Internet of Things into society. Dr. Sourav Banerjee is an Assistant Professor at the Department of Computer Science and Engineering of Kalyani Government Engineering College, Kalyani, West Bengal, India. His research interests include Big Data, Cloud Computing, Distributed Computing and Mobile Communications. Dr. Chinmay Chakraborty is an Assistant Professor at the Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. His main research interests include the Internet of Medical Things, WBAN, Wireless Networks, Telemedicine, m-Health/e-Health and Medical Imaging. Dr. Kousik Dasgupta is an Assistant Professor at the Department of Computer Science and Engineering, Kalyani Government Engineering College, India. His research interests include Computer Vision, AI/ML, Cloud Computing, Big Data and Security.