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


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.




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


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.




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


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.




Artificial Intelligence in Healthcare


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




Management for Digital Transformation


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.




Advances in Computing and Data Sciences


Book Description

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.




Bio-Inspired Algorithms and Devices for Treatment of Cognitive Diseases Using Future Technologies


Book Description

As there are no proper medical tests available to predict certain diseases such as Alzheimer’s and Parkinson’s at an early stage, there is a need to further study and consider the potential uses of bio- and nature-inspired algorithms and future technologies such as machine learning in correlation to disease detection and treatment. Bio-Inspired Algorithms and Devices for Treatment of Cognitive Diseases Using Future Technologies considers new tools for early detection of cognitive brain diseases using devices and algorithms whose basic concept is taken from nature and discusses design, analysis, and application of various bionics or bio-inspired algorithms. Covering topics such as depression and cognitive science, this publication is an ideal resource for researchers, academicians, industry professionals, psychologists, psychiatrists, nurses, engineers, instructors, and students.




Assistive Technologies for Assessment and Recovery of Neurological Impairments


Book Description

People with neurological disorders may experience significant problems, isolation, detachment, and passivity while dealing with environmental requests. They constantly rely on caregivers and family assistance, which can create negative outcomes on their quality of life. An emerging way to overcome these issues is assistive technology-based interventions (AT). AT-based programs are designed to fill the gap between human/individual capacities or skills and environmental requests. These technologies can also bring about independence and self-determination and provide people with neurological disorders an active role, positive participation, and an enhanced status in being able to achieve functional daily activities by reducing the roles of their families and caregivers. The positive impacts of this technology are an important area of research, and its usage for neurological disorders is critical for the assessment and recovery of patients. Assistive Technologies for Assessment and Recovery of Neurological Impairments explores the use of AT-based programs for promoting independence and self-determination of individuals with neurological disorders. The chapters discuss AT-based interventions in detail with the specific technologies that are being used, the positive effects on patients, and evidence-based practices. This book also focuses on specific technologies such as virtual reality (VR) setups and augmented reality (AR) as valid ecological environments for patients that ensure methodological control and behavioral tracking for both assessment and rehabilitation purposes. This book is essential for occupational therapists, speech therapists, physiotherapists, neurologists, caregivers, psychologists, practitioners, medical professionals, medical technologists, IT consultants, academicians, and students interested in assistive technology interventions for people with neurological impairments.




Emerging Advancements for Virtual and Augmented Reality in Healthcare


Book Description

Within the last few years, devices that are increasingly capable of offering an immersive experience close to reality have emerged. As devices decrease in size, the interest and application possibilities for them increase. In the healthcare sector, there is an enormous potential for virtual reality development, as this technology allows, on the one hand, the execution of operations or processes at a distance, decoupling realities; and on the other hand, it offers the possibility of simulation for training purposes, whenever there are contexts of risk to the patient or to the health professional. However, virtual reality devices and immersion in virtual environments still requires some improvement as complaints such as headaches and nausea are still common among users, and so continuous research and development is critical to progress the technology. Emerging Advancements for Virtual and Augmented Reality in Healthcare synthesizes the trends, best practices, methodologies, languages, and tools used to implement virtual reality and create a positive user experience while also discussing how to implement virtual reality into day-to-day work with a focus on healthcare professionals and related areas. The application possibilities and their impact are transversal to all areas of health and fields such as education, training, surgery, pain management, physical rehabilitation, stroke rehabilitation, phobia therapy, and telemedicine. Covering topics such as mental health treatment and virtual simulations, it is ideal for medical professionals, engineers, computer scientists, researchers, practitioners, managers, academicians, teachers, and students.




Recent Advances in Computing Sciences


Book Description

The 1st International Conference on Recent Advances in Computing Sciences (RACS-2022) organized by the School of Computer Application, Lovely Professional University, Jalandhar, Punjab from 4th to 5th November, 2022. The conference focuses on discussing issues, exchanging ideas, and the most recent innovations towards the advancement of research in the field of Computing Sciences and Technology. All technical sessions were predominantly related to Data Science, Artificial Intelligence, Remote Sensing, Image Processing, Computer Vision, Data Forensics, Cyber Security, Computational Sciences, Simulation & Modelling, Business Analytics, and Machine Learning. The main objective of this conference is to provide a common platform for academia and industry to discuss various technological challenges and share cognitive thoughts. It provided a thought-provoking platform to discuss and disseminate novel solutions for real-world problems in a dynamic and changing technological environment. The main success of RACS-2022 is to give an opportunity for the participants to enhance their knowledge of recent computing technologies.