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Author: Roy, Manikant
Publisher: IGI Global
ISBN: 1799871908
Category : Computers
Languages : en
Pages : 241
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Book Description
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.
Author: Roy, Manikant
Publisher: IGI Global
ISBN: 1799871908
Category : Computers
Languages : en
Pages : 241
Get Book Here
Book Description
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.
Author: Milutinovi?, Veljko
Publisher: IGI Global
ISBN: 1799883523
Category : Computers
Languages : en
Pages : 296
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Book Description
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.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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Book Description
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
Author: Mundada, Monica R.
Publisher: IGI Global
ISBN: 1799881636
Category : Computers
Languages : en
Pages : 293
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Book Description
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.
Author: Abhishek Swaroop
Publisher: Springer Nature
ISBN: 9819965500
Category : Technology & Engineering
Languages : en
Pages : 686
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Book Description
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.
Author: Karthikeyan, P.
Publisher: IGI Global
ISBN: 1668457245
Category : Computers
Languages : en
Pages : 326
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Book Description
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.
Author: Nitin Naik
Publisher: Springer Nature
ISBN: 3031744438
Category :
Languages : en
Pages : 826
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Book Description
Author: Hasmat Malik
Publisher: Springer Nature
ISBN: 9813344121
Category : Technology & Engineering
Languages : en
Pages : 522
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Book Description
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.
Author: Carolina Machado
Publisher: Springer Nature
ISBN: 3031420608
Category : Technology & Engineering
Languages : en
Pages : 226
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Book Description
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.
Author: Nijalingappa, Pradeep
Publisher: IGI Global
ISBN: 1799884457
Category : Medical
Languages : en
Pages : 282
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Book Description
Machine learning approaches have great potential in increasing the accuracy of cardiovascular risk prediction and avoiding unnecessary treatment. The application of machine learning techniques may improve heart failure outcomes and management, including cost savings by improving existing diagnostic and treatment support systems. Additionally, artificial intelligence technologies can assist physicians in making better clinical decisions, enabling early detection of subclinical organ dysfunction, and improving the quality and efficiency of healthcare delivery. Further study on these innovative technologies is required in order to appropriately utilize the technology in healthcare. Leveraging AI Technologies for Preventing and Detecting Sudden Cardiac Arrest and Death provides insight into the causes and symptoms of sudden cardiac death and sudden cardiac arrest while evaluating whether artificial intelligence technologies can improve the accuracy of cardiovascular risk prediction. Furthermore, it consolidates the current open issues and future technology-driven solutions for sudden cardiac death and sudden cardiac arrest prevention and detection. Covering a number of crucial topics such as wearable sensors and smart technologies, this reference work is ideal for diagnosticians, IT specialists, data scientists, healthcare workers, researchers, academicians, scholars, practitioners, instructors, and students.
