Biomedical And Business Applications Using Artificial Neural Networks And Machine Learning
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| Author | : Segall, Richard S. |
| Publisher | : IGI Global |
| Total Pages | : 394 |
| Release | : 2022-01-07 |
| Genre | : Computers |
| ISBN | : 1799884570 |
During these uncertain and turbulent times, intelligent technologies including artificial neural networks (ANN) and machine learning (ML) have played an incredible role in being able to predict, analyze, and navigate unprecedented circumstances across a number of industries, ranging from healthcare to hospitality. Multi-factor prediction in particular has been especially helpful in dealing with the most current pressing issues such as COVID-19 prediction, pneumonia detection, cardiovascular diagnosis and disease management, automobile accident prediction, and vacation rental listing analysis. To date, there has not been much research content readily available in these areas, especially content written extensively from a user perspective. Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning is designed to cover a brief and focused range of essential topics in the field with perspectives, models, and first-hand experiences shared by prominent researchers, discussing applications of artificial neural networks (ANN) and machine learning (ML) for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence. It also presents summaries of currently available open source software that utilize neural networks and machine learning. The book is ideal for professionals, researchers, students, and practitioners who want to more fully understand in a brief and concise format the realm and technologies of artificial neural networks (ANN) and machine learning (ML) and how they have been used for prediction of multi-disciplinary research problems in a multitude of disciplines.
| Author | : Jorge Garza Ulloa |
| Publisher | : Elsevier |
| Total Pages | : 704 |
| Release | : 2021-11-29 |
| Genre | : Science |
| ISBN | : 0128207183 |
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®. Provides an introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems Explain different Artificial Intelligence (AI) including evolutionary algorithms to emulate natural evolution, reinforced learning, Artificial Neural Network (ANN) type and cognitive learning and to obtain many AI models for Biomedical Engineering problems Includes coverage of the evolution Artificial Intelligence through Machine Learning (ML), Deep Learning (DL), Cognitive Computing (CC) using MATLAB® as a programming language with many add-on MATLAB® toolboxes, and AI based commercial products cloud services as: IBM (Cognitive Computing, IBM Watson®, IBM Watson Studio®, IBM Watson Studio Visual Recognition®), and others Provides the necessary tools to accelerate obtaining results for the analysis of injuries, illness, and neurologic diseases that can be detected through the static, kinetics and kinematics, and natural body language data and medical imaging techniques applying AI using ML-DL-CC algorithms with the objective of obtaining appropriate conclusions to create solutions that improve the quality of life of patients
| Author | : Adam Bohr |
| Publisher | : Academic Press |
| Total Pages | : 385 |
| Release | : 2020-06-21 |
| Genre | : Computers |
| ISBN | : 0128184396 |
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 | : Utku Kose |
| Publisher | : CRC Press |
| Total Pages | : 365 |
| Release | : 2021-07-19 |
| Genre | : Technology & Engineering |
| ISBN | : 1000406423 |
This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.
| Author | : Easwaran, Balamurugan |
| Publisher | : IGI Global |
| Total Pages | : 307 |
| Release | : 2022-03-11 |
| Genre | : Computers |
| ISBN | : 1799893103 |
Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.
| Author | : Management Association, Information Resources |
| Publisher | : IGI Global |
| Total Pages | : 1953 |
| Release | : 2022-08-05 |
| Genre | : Business & Economics |
| ISBN | : 1668474611 |
The COVID-19 pandemic has shocked economies around the world and created an era of global instability. As the pandemic comes to a close, it is essential to examine global economies in order to achieve and maintain global stability. By maintaining global stability, the world may be prepared for future economic shocks. The Research Anthology on Macroeconomics and the Achievement of Global Stability discusses the emerging opportunities, challenges, and strategies within the field of macroeconomics. It features advancements in the field that encourage global economic stability. Covering topics such as Islamic banking, international trade, and Econophysics, this major reference work is an ideal resource for economists, government leaders and officials, business leaders and executives, finance professionals, students and educators of higher education, librarians, researchers, and academicians.
| Author | : Nayyar, Anand |
| Publisher | : IGI Global |
| Total Pages | : 284 |
| Release | : 2022-04-22 |
| Genre | : Computers |
| ISBN | : 1799890147 |
Computational science, in collaboration with engineering, acts as a bridge between hypothesis and experimentation. It is essential to use computational methods and their applications in order to automate processes as many major industries rely on advanced modeling and simulation. Computational science is inherently interdisciplinary and can be used to identify and evaluate complicated systems, foresee their performance, and enhance procedures and strategies. Applications of Computational Science in Artificial Intelligence delivers technological solutions to improve smart technologies architecture, healthcare, and environmental sustainability. It also provides background on key aspects such as computational solutions, computation framework, smart prediction, and healthcare solutions. Covering a range of topics such as high-performance computing and software infrastructure, this reference work is ideal for software engineers, practitioners, researchers, scholars, academicians, instructors, and students.
| Author | : Catalán Pallarés, Sandra |
| Publisher | : IGI Global |
| Total Pages | : 279 |
| Release | : 2022-10-14 |
| Genre | : Mathematics |
| ISBN | : 1799870847 |
Optimized linear algebra (LA) libraries that are able to exploit the underlying hardware are always of interest in the high-performance computing community. The implementation of LA software has evolved along with computer architecture, while the specification remains unaltered almost from the beginning. It is important to differentiate between the specification of LA libraries and their implementation. Because LA libraries pursue high performance, the implementation for a given architecture needs to be optimized for it specifically. However, the type of operations included in the libraries, the input/output parameters, and the data types to be handled are common to all of them. This is why, while the specification remains constant, the implementation evolves with the creation of new architectures. Developing Linear Algebra Codes on Modern Processors: Emerging Research and Opportunities presents the main characteristics of LA libraries, showing the differences between the standards for sparse and dense versions. It further explores relevant linear algebra problems and shows, in a clear and understandable way, how to solve them using different computer architectures. Covering topics such as programming models, batched computing, and distributed memory platforms, this premier reference source is an excellent resource for programmers, computer scientists, engineers, students and faculty of higher education, librarians, researchers, and academicians.
| Author | : Beneventi, Paolo |
| Publisher | : IGI Global |
| Total Pages | : 283 |
| Release | : 2024-01-30 |
| Genre | : Computers |
| ISBN | : 1668482304 |
In our fast-paced, technology-driven world, there is a strong sense of untapped potential and unfulfilled promises. People today possess an unprecedented amount of power through their technological gadgets but often remain unaware of how to wield it effectively. This lack of understanding and agency leads to a plethora of societal problems, from passive consumerism to environmental degradation, fostering a sense of helplessness. Considerations of Cyber Behavior and Mass Technology in Modern Society offer a comprehensive solution to this pressing issue. It is a scholarly beacon, guiding academic scholars and critical thinkers toward a profound reassessment of our relationship with technology and society. By delving into the intricate web of topics such as active citizenship, global information production, and the coexistence of consumer technology and freedom, our book presents an opportunity to explore the root causes of our modern-day challenges.
| Author | : Kane, Lalit |
| Publisher | : IGI Global |
| Total Pages | : 249 |
| Release | : 2022-03-25 |
| Genre | : Computers |
| ISBN | : 1799894363 |
Due to the rise of new applications in electronic appliances and pervasive devices, automated hand gesture recognition (HGR) has become an area of increasing interest. HGR developments have come a long way from the traditional sign language recognition (SLR) systems to depth and wearable sensor-based electronic devices. Where the former are more laboratory-oriented frameworks, the latter are comparatively realistic and practical systems. Based on various gestural traits, such as hand postures, gesture recognition takes different forms. Consequently, different interpretations can be associated with gestures in various application contexts. A considerable amount of research is still needed to introduce more practical gesture recognition systems and associated algorithms. Challenges and Applications for Hand Gesture Recognition highlights the state-of-the-art practices of HGR research and discusses key areas such as challenges, opportunities, and future directions. Covering a range of topics such as wearable sensors and hand kinematics, this critical reference source is ideal for researchers, academicians, scholars, industry professionals, engineers, instructors, and students.
