Author: Cristina Oyarzun Laura Publisher: Springer Nature ISBN: 3030908747 Category : Computers Languages : en Pages : 201
Book Description
This book constitutes the refereed proceedings of the 10th International Workshop on Clinical Image-Based Procedures, CLIP 2021, Second MICCAI Workshop on Distributed and Collaborative Learning, DCL 2021, First MICCAI Workshop, LL-COVID19, First Secure and Privacy-Preserving Machine Learning for Medical Imaging Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. CLIP 2021 accepted 9 papers from the 13 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice. For DCL 2021, 4 papers from 7 submissions were accepted for publication. They deal with machine learning applied to problems where data cannot be stored in centralized databases and information privacy is a priority. LL-COVID19 2021 accepted 2 papers out of 3 submissions dealing with the use of AI models in clinical practice. And for PPML 2021, 2 papers were accepted from a total of 6 submissions, exploring the use of privacy techniques in the medical imaging community.
Author: Ruidan Su Publisher: Springer Nature ISBN: 9811667756 Category : Technology & Engineering Languages : en Pages : 567
Book Description
This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging. Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.
Author: Manju Publisher: Springer Nature ISBN: 3031419251 Category : Computers Languages : en Pages : 208
Book Description
This book explores new applications in the field of science and technology for healthcare systems. The main focus of this book is to devise smart, efficient and robust solutions for the health care sector to serve the major population of rural areas. Artificial Intelligence-based Healthcare Systems encourages scientists, engineers, and scholars across the multiple disciplines to design smart intelligent innovations on rural healthcare issues and motivate to collaborate multiple ideas to design best solutions. It also helps the readers at various levels of knowledge to further enhance their understanding for new tools and smart solutions.
Author: Hayit Greenspan Publisher: Academic Press ISBN: 9780323901079 Category : Computers Languages : en Pages : 350
Book Description
Medical imaging is playing a role in the fight against COVID-19, in some countries as a key tool, from the screening and diagnosis through the entire treatment procedure. The extraordinarily rapid spread of this pandemic has demonstrated that a new disease entity with a subset of relatively unique characteristics can pose a major new clinical challenge that requires new diagnostic tools in imaging. The AI/Deep Learning Imaging community has shown in many recent publications that rapidly developed AI-based automated CT and Xray image analysis tools can achieve high accuracy in detection of Coronavirus positive patients as well as quantifying the disease burden. The typical developmental cycle and large number of studies required to develop AI algorithms for various disease entities is much too long to respond effectively to produce these software tools on demand. This suggests the strong need to develop software more rapidly, perhaps using transfer learning from existing algorithms, to train on a relatively limited number of cases, and to train on multiple datasets in various locations that may not be able to be easily combined due to privacy and security issues. Deep Learning for COVID Image Analysis provides a comprehensive overview of the most recently developed deep learning-based systems and solutions for COVID-19 image analysis, assembling a collection of state-of-the-art works for detection, severity analysis and predictive analysis, all of which are tools to support handling of the disease. Provides a comprehensive overview of research work on deep learning for COVID-19 image analysis Offers proven deep learning algorithms for medical image analysis applications Presents the research challenges in approaching a new disease
Author: Mohamed Lahby Publisher: Springer Nature ISBN: 3031286316 Category : Technology & Engineering Languages : en Pages : 397
Book Description
This book presents the latest research, theoretical methods, and novel applications in the field of Health 5.0. The authors focus on combating COVID-19 or other pandemics through facilitating various technological services. The authors discuss new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 or other pandemic based on machine intelligence models and communication technologies. The aim of the coverage is to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence and Internet of Medical Things (IoMT). This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics.
Author: Fadi Al-Turjman Publisher: Springer Nature ISBN: 3030601889 Category : Technology & Engineering Languages : en Pages : 266
Book Description
This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies.
Author: Amit Joshi Publisher: Springer Nature ISBN: 9811565724 Category : Technology & Engineering Languages : en Pages : 91
Book Description
This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.
Author: Parag Chatterjee Publisher: Elsevier ISBN: 0323905730 Category : Computers Languages : en Pages : 226
Book Description
Artificial Intelligence in Healthcare and COVID-19 showcases theoretical concepts and implementational and research perspectives surrounding AI. The book addresses both medical and technological visions, making it even more applied. With the advent of COVID-19, it is obvious that leading universities and medical schools must include these topics and case studies in their usual courses of health informatics to keep up with the pace of technological and medical advancements. This book will also serve professors teaching courses and industry practitioners and professionals working in the R&D team of leading medical and informatics companies who want to embrace AI and eHealth to fight COVID-19. Since AI in healthcare is a comparatively new field, there exists a vacuum of literature in this field, especially when applied to COVID-19. With the area of AI in COVID-19 being quite young, students and researchers usually face a struggle to rely on the few published papers (which are obviously too specific) or whitepapers by tech-giants (which are too wide). Discusses the fundamentals and theoretical concepts of applying AI in healthcare pertaining to COVID-19 Provides a landscape view to the applied aspect of AI in healthcare related COVID-19 through case studies and innovative applications Discusses key concerns and challenges in the field of AI in eHealth during the pandemic, along with other allied fields like IoT, creating a broad platform of transdisciplinary discussion
Author: Anusha Kostka Publisher: OrangeBooks Publication ISBN: Category : Education Languages : en Pages : 94
Book Description
"Artificial Intelligence in Healthcare: A Compilation of Case Studies" offers a comprehensive view of AI's transformative impact on healthcare. Delving into applications and challenges, the book showcases detailed case studies illuminating AI's role in diagnosis, treatment, prevention, and management. From early cancer detection to personalized medicine, each case study exemplifies AI's potential to improve patient outcomes. Ethical dilemmas and emerging trends in AI research are also explored, providing a holistic view of AI's future in healthcare. This book is an essential guide for researchers, healthcare professionals, and anyone intrigued by AI's potential to revolutionize healthcare delivery.
Author: Shadi Albarqouni Publisher: Springer Nature ISBN: 3031185234 Category : Computers Languages : en Pages : 215
Book Description
This book constitutes the refereed proceedings of the Third MICCAI Workshop on Distributed, Collaborative, and Federated Learning, DeCaF 2022, and the Second MICCAI Workshop on Affordable AI and Healthcare, FAIR 2022, held in conjunction with MICCAI 2022, in Singapore in September 2022. FAIR 2022 was held as a hybrid event. DeCaF 2022 accepted 14 papers from the 18 submissions received. The workshop aims at creating a scientific discussion focusing on the comparison, evaluation, and discussion of methodological advancement and practical ideas about machine learning applied to problems where data cannot be stored in centralized databases or where information privacy is a priority. For FAIR 2022, 4 papers from 9 submissions were accepted for publication. The topics of the accepted submissions focus on deep ultrasound segmentation, portable OCT image quality enhancement, self-attention deep networks and knowledge distillation in low-regime setting.
Author: Cristina Oyarzun Laura
Author: Ruidan Su
Author: Manju
Author: Hayit Greenspan
Author: Mohamed Lahby
Author: Fadi Al-Turjman
Author: Amit Joshi
Author: Parag Chatterjee
Author: Anusha Kostka
Author: Shadi Albarqouni