Download or read book Approaches and Applications of Deep Learning in Virtual Medical Care written by Zaman, Noor and published by IGI Global. This book was released on 2022-02-25 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent advancements in the machine learning paradigm have various applications, specifically in the field of medical data analysis. Research has proven the high accuracy of deep learning algorithms, and they have become a standard choice for analyzing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Approaches and Applications of Deep Learning in Virtual Medical Care considers the applications of deep learning in virtual medical care and delves into complex deep learning algorithms, calibrates models, and improves the predictions of the trained model on medical imaging. Covering topics such as big data and medical sensors, this critical reference source is ideal for researchers, academicians, practitioners, industry professionals, hospital workers, scholars, instructors, and students.

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

Download or read book Applications of Deep Learning and Big IoT on Personalized Healthcare Services written by Wason, Ritika and published by IGI Global. This book was released on 2020-02-07 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes. Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.

Download or read book Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics written by Abhishek Kumar and published by CRC Press. This book was released on 2022-03-09 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.

Download or read book Digital Twins and Healthcare Trends Techniques and Challenges written by Gaur, Loveleen and published by IGI Global. This book was released on 2022-11-25 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: The healthcare industry is starting to adopt digital twins to improve personalized medicine, healthcare organization performance, and new medicine and devices. These digital twins can create useful models based on information from wearable devices, omics, and patient records to connect the dots across processes that span patients, doctors, and healthcare organizations as well as drug and device manufacturers. Digital twins are digital representations of human physiology built on computer models. The use of digital twins in healthcare is revolutionizing clinical processes and hospital management by enhancing medical care with digital tracking and advancing modelling of the human body. These tools are of great help to researchers in studying diseases, new drugs, and medical devices. Digital Twins and Healthcare: Trends, Techniques, and Challenges facilitates the advancement and knowledge dissemination in methodologies and applications of digital twins in the healthcare and medicine fields. This book raises interest and awareness of the uses of digital twins in healthcare in the research community. Covering topics such as deep neural network, edge computing, and transfer learning method, this premier reference source is an essential resource for hospital administrators, pharmacists, medical professionals, IT consultants, students and educators of higher education, librarians, and researchers.

Download or read book Deep Learning for Biomedical Applications written by Utku Kose and published by CRC Press. This book was released on 2021-07-19 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book AI Techniques for Securing Medical and Business Practices written by Jhanjhi, Noor Zaman and published by IGI Global. This book was released on 2024-09-27 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past several years, artificial intelligence (AI) has upended and transformed the private and public sectors. AI techniques have shown significant promise in securing sensitive data and ensuring compliance with regulatory standards. In medical practices, AI can enhance patient confidentiality through advanced encryption methods. Similarly, in business environments, AI-driven security protocols can protect against cyber threats and unauthorized access, safeguarding both intellectual property and customer information. By leveraging AI for these purposes, organizations can not only enhance their operational efficiency but also build trust and credibility with their stakeholders. AI Techniques for Securing Medical and Business Practices provides real-world case studies and cutting-edge research to demonstrate how AI is enhancing threat detection and risk management in cybersecurity. Beyond cybersecurity, this book explores the broader applications of AI in fields such as healthcare, finance, and creative industries. It examines innovations in medical imaging, financial modeling, and content creation, while addressing critical ethical issues like data privacy and algorithmic bias. Aimed at researchers, postgraduate scholars, industry professionals, and the general public, it provides a thorough understanding of AI's transformative potential and its implications for various sectors.

Download or read book Applied Artificial Intelligence written by Swati V. Shinde and published by CRC Press. This book was released on 2023-09-29 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems. Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images. The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.

Download or read book Proceedings of 3rd International Conference on Mathematical Modeling and Computational Science written by Sheng-Lung Peng and published by Springer Nature. This book was released on 2023-08-28 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume is a collection of high-quality, peer-reviewed research papers presented at the Third International Conference on Mathematical Modeling and Computational Science (ICMMCS 2023), held during 24 – 25 February 2023 in hybrid mode. The topics covered in the book are mathematical logic and foundations, numerical analysis, neural networks, fuzzy set theory, coding theory, higher algebra, number theory, graph theory and combinatory, computation in complex networks, calculus, differential educations and integration, application of soft computing, knowledge engineering, machine learning, artificial intelligence, big data and data analytics, high performance computing, network and device security, Internet of Things (IoT).

Download or read book AI and Neuro Degenerative Diseases written by Loveleen Gaur and published by Springer Nature. This book was released on with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning in Personalized Healthcare and Decision Support written by Harish Garg and published by Elsevier. This book was released on 2023-07-20 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available. This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth. - Discusses the application of deep learning in several areas of healthcare, including clinical trials, telemedicine and health records management - Brings together experts in the intersection of deep learning, medicine, healthcare and programming to cover topics in an interdisciplinary way - Uncovers the stakes and possibilities involved in realizing personalized healthcare services through efficient and effective deep learning technologies

Download or read book Federated Learning written by Qiang Yang and published by Springer Nature. This book was released on 2020-11-25 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”

Download or read book Computational Analysis and Deep Learning for Medical Care written by Amit Kumar Tyagi and published by John Wiley & Sons. This book was released on 2021-08-24 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.

Download or read book Deep Learning Applications Volume 2 written by M. Arif Wani and published by Springer. This book was released on 2020-12-14 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.

Download or read book Applications of Machine Learning written by Prashant Johri and published by Springer Nature. This book was released on 2020-05-04 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

Download or read book Applications of Machine Learning in UAV Networks written by Hassan, Jahan and published by IGI Global. This book was released on 2024-01-17 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy. This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond.

Download or read book Handbook of AI Based Models in Healthcare and Medicine written by Bhanu Chander and published by CRC Press. This book was released on 2024-02-21 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides thorough, in-depth, and well-focused developments of artificial intelligence (AI), machine learning (ML), deep learning (DL), natural language processing (NLP), cryptography, and blockchain approaches, along with their applications focused on healthcare systems. Handbook of AI-Based Models in Healthcare and Medicine: Approaches, Theories, and Applications highlights different approaches, theories, and applications of intelligent systems from a practical as well as a theoretical view of the healthcare domain. It uses a medically oriented approach in its discussions of human biology, healthcare, and medicine and presents NLP-based medical reports and medicine enhancements. The handbook includes advanced models of ML and DL for the management of healthcare systems and also discusses blockchain-based healthcare management. In addition, the handbook offers use cases where AI, ML, and DL can help solve healthcare complications. Undergraduate and postgraduate students, academicians, researchers, and industry professionals who have an interest in understanding the applications of ML/DL in the healthcare setting will want this reference on their bookshelf.