Author : Feng Gao
Publisher : Frontiers Media SA
Page : 402 pages
File Size : 45,57 MB
Release : 2023-04-24
Category : Science
ISBN : 2832521304
Author : Adam Bohr
Publisher : Academic Press
Page : 385 pages
File Size : 30,81 MB
Release : 2020-06-21
Category : 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 : Michael Mahler
Publisher : Academic Press
Page : 302 pages
File Size : 23,21 MB
Release : 2021-03-12
Category : Science
ISBN : 032385432X
Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. - Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions - Provides background, milestone and examples of precision medicine - Outlines the paradigm shift towards precision medicine driven by value-based systems - Discusses future applications of precision medicine research using AI - Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine
Author : Subhi J. Al'Aref, M.D.
Publisher : Academic Press
Page : 454 pages
File Size : 40,90 MB
Release : 2020-12-11
Category : Medical
ISBN : 0128202734
Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach
Author : Sai Kiran Oruganti
Publisher : CRC Press
Page : 392 pages
File Size : 14,2 MB
Release : 2024-07-01
Category : Technology & Engineering
ISBN : 1040046819
The Industrial Internet of Things (IIoT) has become an effective tool with significant implications for industrialisation and Market Research (MR), especially in the field of green production. Green IIoT (GRIIoT) can be used to implement Green Production (GP) goals for the environment. The purpose of this study is to examine the drivers behind the adoption of GIIoT, MR, and industrialization decision-making, as well as the effects these drivers have on industrialization performance (IP). A structured questionnaire was used to gather information in order to evaluate the suggested study paradigm. The results indicate that institutional isomorphism influences the acceptance of GRIIoT in a favorable way. Furthermore, Green innovation (GI) activities that result in IP are favorably correlated with GIIoT. The potential effects of the various institutional isomorphisms discussed in this study can aid organizations in better understanding the responsibilities to protect and satisfying stakeholders, particularly as the adopt GIIoT to handle production problems and possible accordance pressures in the process.
Author : David Riaño
Publisher : Springer
Page : 431 pages
File Size : 39,60 MB
Release : 2019-06-19
Category : Computers
ISBN : 303021642X
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.
Author : Joy Higgs
Publisher : Elsevier Health Sciences
Page : 518 pages
File Size : 43,16 MB
Release : 2008-02-14
Category : Medical
ISBN : 0750688858
Clinical reasoning is the foundation of professional clinical practice. Totally revised and updated, this book continues to provide the essential text on the theoretical basis of clinical reasoning in the health professions and examines strategies for assisting learners, scholars and clinicians develop their reasoning expertise. key chapters revised and updated nature of clinical reasoning sections have been expanded increase in emphasis on collaborative reasoning core model of clinical reasoning has been revised and updated
Author : Kaushal Kishor
Publisher : CRC Press
Page : 275 pages
File Size : 11,27 MB
Release : 2024-10-30
Category : Computers
ISBN : 1040146317
The effectiveness of federated learning in high‐performance information systems and informatics‐based solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoT‐based human activity recognition to show the efficacy of personalized federated learning for intelligent IoT applications. Features: • Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users’ privacy. • Describes how federated learning may assist in understanding and learning from user behavior in IoT applications while safeguarding user privacy. • Presents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the area. • Analyses the need for a personalized federated learning framework in cloud‐edge and wireless‐edge architecture for intelligent IoT applications. • Comprises real‐life case illustrations and examples to help consolidate understanding of topics presented in each chapter. This book is recommended for anyone interested in federated learning‐based intelligent algorithms for smart communications.
Author : Khang, Alex
Publisher : IGI Global
Page : 479 pages
File Size : 31,86 MB
Release : 2024-03-04
Category : Medical
ISBN :
While ultra-high field strength diagnosis technologies and artificial intelligence have propelled medicine imaging towards microstructure analysis and precise medicine, persistent challenges remain. These range from long scanning times to motion sensitivity and issues with imaging quality for certain types of tissue. Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry summarizes emerging techniques, outlines clinical applications, and confronts the challenges head-on, proposing avenues for further research. It explores emerging techniques such as human-like robotics, medical Internet of Things (IoT), low-cost CT scanners, portable MRI devices, and breakthroughs in diagnosis technologies like zero echo time (ZTM) and compressed sensing volume interpolation breath-holding test sequences (CS-VIBE). This book provides an overview of the current state of medical imaging and clinical diagnosis applications, then expands into a roadmap for the future, envisioning the seamless integration of medical robotics and AI-assisted applications in the high-tech healthcare industry. As the influence of artificial intelligence continues to grow, the book serves as a clarion call for collaborative efforts, increased research, and unified strategies to navigate the challenges and harness the opportunities presented by the high-tech medical industry. This book is ideal for medical analysts, healthcare scientists, biotechnology analysts, scholars, researchers, academics, professionals, engineers, and students worldwide.
Author : Sinha, Amit
Publisher : IGI Global
Page : 512 pages
File Size : 10,52 MB
Release : 2024-10-30
Category : Medical
ISBN :
The constantly evolving healthcare industry has experienced tremendous technological advancements that have significantly revolutionized medical imaging. However, with the increasing volume and complexity of medical image data, existing analysis methods must also be updated to be efficient and accurate. This is where the challenge lies—a need for a comprehensive solution that bridges the gap between cutting-edge technology and effective healthcare delivery. Computer-Assisted Analysis for Digital Medicinal Imagery offers a roadmap for navigating the intricate landscape of digital medicinal imagery analysis. Unlocking the power of machine learning and breaking down the basics provides researchers, clinicians, and students with the tools necessary to harness technology and improve healthcare outcomes.
