Clinical Image Based Procedures Distributed And Collaborative Learning Artificial Intelligence For Combating Covid 19 And Secure And Privacy Preserving Machine Learning

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Clinical Image Based Procedures Distributed And Collaborative Learning Artificial Intelligence For Combating Covid 19 And Secure And Privacy Preserving Machine Learning
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Author : Cristina Oyarzun Laura
language : en
Publisher: Springer Nature
Release Date : 2021-11-13
Clinical Image Based Procedures Distributed And Collaborative Learning Artificial Intelligence For Combating Covid 19 And Secure And Privacy Preserving Machine Learning written by Cristina Oyarzun Laura and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-13 with Computers categories.
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.
Medical Imaging And Computer Aided Diagnosis
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Author : Ruidan Su
language : en
Publisher: Springer Nature
Release Date : 2023-12-19
Medical Imaging And Computer Aided Diagnosis written by Ruidan Su and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-19 with Technology & Engineering categories.
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.
Proceedings Of Fifth International Conference On Computing Communications And Cyber Security
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Author : Sudeep Tanwar
language : en
Publisher: Springer Nature
Release Date : 2024-07-30
Proceedings Of Fifth International Conference On Computing Communications And Cyber Security written by Sudeep Tanwar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-30 with Technology & Engineering categories.
This book features selected research papers presented at the Fifth International Conference on Computing, Communications, and Cyber-Security (IC4S'05), organized in India, during 29 February to 1 March, 2024. The conference was hosted at SMVDU, Katra, J&K, India . It includes innovative work from researchers, leading innovators, and professionals in the areas of communication and network technologies, advanced computing technologies, data analytics and intelligent learning, the latest electrical and electronics trends, and security and privacy issues. The work is presented in two volumes.
Artificial Intelligence Based Healthcare Systems
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Author : Manju
language : en
Publisher: Springer Nature
Release Date : 2023-12-02
Artificial Intelligence Based Healthcare Systems written by Manju and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-02 with Computers categories.
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.
Clinical Image Based Procedures Distributed And Collaborative Learning Artificial Intelligence For Combating Covid 19 And Secure And Privacy Preserving Machine Learning
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Author : Cristina Oyarzun Laura
language : en
Publisher: Springer
Release Date : 2021-11-14
Clinical Image Based Procedures Distributed And Collaborative Learning Artificial Intelligence For Combating Covid 19 And Secure And Privacy Preserving Machine Learning written by Cristina Oyarzun Laura and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-14 with Computers categories.
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.
Ai Enabled Data Science For Covid 19
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Author : Da Yan
language : en
Publisher: Frontiers Media SA
Release Date : 2022-01-13
Ai Enabled Data Science For Covid 19 written by Da Yan and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-13 with Science categories.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
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
Responsible Artificial Intelligence
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Author : Virginia Dignum
language : en
Publisher: Springer Nature
Release Date : 2019-11-04
Responsible Artificial Intelligence written by Virginia Dignum and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-04 with Computers categories.
In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens.
Models For Infectious Human Diseases
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Author : Valerie Isham
language : en
Publisher: Cambridge University Press
Release Date : 1996-03-29
Models For Infectious Human Diseases written by Valerie Isham and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-03-29 with Mathematics categories.
Infectious disease accounts for more death and disability globally than either non-infectious disease or injury. This book contains a breadth of different quantitative approaches to understanding the patterns of infectious diseases in populations, and the design of control strategies to lessen their effect. The contributors bring a great variety of mathematical expertise (including deterministic and stochastic modelling and statistical data analysis) and involvement in a wide range of applied fields across the spectrum of biological, medical and social sciences. The aim is to increase interaction between specialities by describing research on many of the infectious diseases that affect humans, including both viral diseases like measles and AIDS and tropical parasitic infections. The papers are divided into groups dealing with problems relating to transmissible diseases, vaccination strategies, the consequences of treatment interventions, the dynamics of immunity, heterogeneity of populations, and prediction.
Federated Learning
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Author : Qiang Yang
language : en
Publisher: Springer Nature
Release Date : 2020-11-25
Federated Learning written by Qiang Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Computers categories.
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.”