Distributed Collaborative And Federated Learning And Affordable Ai And Healthcare For Resource Diverse Global Health

Author : Shadi Albarqouni,Spyridon Bakas,Sophia Bano,M. Jorge Cardoso,Bishesh Khanal,Bennett Landman,Xiaoxiao Li,Chen Qin,Islem Rekik,Nicola Rieke,Holger Roth,Debdoot Sheet,Daguang Xu
Publisher : Springer Nature
Page : 215 pages
File Size : 55,8 Mb
Release : 2022-10-08
Category : Computers
ISBN : 9783031185236

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Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health by Shadi Albarqouni,Spyridon Bakas,Sophia Bano,M. Jorge Cardoso,Bishesh Khanal,Bennett Landman,Xiaoxiao Li,Chen Qin,Islem Rekik,Nicola Rieke,Holger Roth,Debdoot Sheet,Daguang Xu Pdf

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 : M. Emre Celebi,Md Sirajus Salekin,Hyunwoo Kim,Shadi Albarqouni,Catarina Barata,Allan Halpern,Philipp Tschandl,Marc Combalia,Yuan Liu,Ghada Zamzmi,Joshua Levy,Huzefa Rangwala,Annika Reinke,Diya Wynn,Bennett Landman,Won-Ki Jeong,Yiqing Shen,Zhongying Deng,Spyridon Bakas,Xiaoxiao Li,Chen Qin,Nicola Rieke,Holger Roth,Daguang Xu
Publisher : Springer Nature
Page : 397 pages
File Size : 42,5 Mb
Release : 2023-11-30
Category : Computers
ISBN : 9783031474019

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops by M. Emre Celebi,Md Sirajus Salekin,Hyunwoo Kim,Shadi Albarqouni,Catarina Barata,Allan Halpern,Philipp Tschandl,Marc Combalia,Yuan Liu,Ghada Zamzmi,Joshua Levy,Huzefa Rangwala,Annika Reinke,Diya Wynn,Bennett Landman,Won-Ki Jeong,Yiqing Shen,Zhongying Deng,Spyridon Bakas,Xiaoxiao Li,Chen Qin,Nicola Rieke,Holger Roth,Daguang Xu Pdf

This double volume set LNCS 14393-14394 constitutes the proceedings from the workshops held at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2023 Workshops, which took place in Vancouver, BC, Canada, in October 2023. The 54 full papers together with 14 short papers presented in this volume were carefully reviewed and selected from 123 submissions from all workshops. The papers of the workshops are presenting the topical sections: Eighth International Skin Imaging Collaboration Workshop (ISIC 2023) First Clinically-Oriented and Responsible AI for Medical Data Analysis (Care-AI 2023) Workshop First International Workshop on Foundation Models for Medical Artificial General Intelligence (MedAGI 2023) Fourth Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2023) First MICCAI Workshop on Time-Series Data Analytics and Learning First MICCAI Workshop on Lesion Evaluation and Assessment with Follow-Up (LEAF) AI For Treatment Response Assessment and predicTion Workshop (AI4Treat 2023) Fourth International Workshop on Multiscale Multimodal Medical Imaging (MMMI 2023) Second International Workshop on Resource-Effcient Medical Multimodal Medical Imaging Image Analysis (REMIA 2023)

Author : Nathan Gaw
Publisher : Springer Nature
Page : 388 pages
File Size : 40,7 Mb
Release : 2024-06-28
Category : Electronic
ISBN : 9783031530920

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Multimodal and Tensor Data Analytics for Industrial Systems Improvement by Nathan Gaw Pdf

Author : Qiang Qiang Yang,Yang Yang Liu,Yong Yong Cheng,Yan Yan Kang,Tianjian Tianjian Chen,Han Han Yu
Publisher : Springer Nature
Page : 189 pages
File Size : 40,6 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031015854

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Federated Learning by Qiang Qiang Yang,Yang Yang Liu,Yong Yong Cheng,Yan Yan Kang,Tianjian Tianjian Chen,Han Han Yu Pdf

How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.

Author : Shadi Albarqouni,M. Jorge Cardoso,Qi Dou,Konstantinos Kamnitsas,Bishesh Khanal,Islem Rekik,Nicola Rieke,Debdoot Sheet,Sotirios Tsaftaris,Daguang Xu,Ziyue Xu
Publisher : Unknown
Page : 0 pages
File Size : 52,9 Mb
Release : 2021
Category : Electronic
ISBN : 303087723X

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Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health by Shadi Albarqouni,M. Jorge Cardoso,Qi Dou,Konstantinos Kamnitsas,Bishesh Khanal,Islem Rekik,Nicola Rieke,Debdoot Sheet,Sotirios Tsaftaris,Daguang Xu,Ziyue Xu Pdf

This book constitutes the refereed proceedings of the Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with MICCAI 2021, in September/October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. DART 2021 accepted 13 papers from the 21 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. For FAIR 2021, 10 papers from 17 submissions were accepted for publication. They focus on Image-to-Image Translation particularly for low-dose or low-resolution settings; Model Compactness and Compression; Domain Adaptation and Transfer Learning; Active, Continual and Meta-Learning. .

Author : Muhammad Habib ur Rehman,Mohamed Medhat Gaber
Publisher : Springer Nature
Page : 207 pages
File Size : 50,9 Mb
Release : 2021-06-11
Category : Technology & Engineering
ISBN : 9783030706043

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Federated Learning Systems by Muhammad Habib ur Rehman,Mohamed Medhat Gaber Pdf

This book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.

Author : Agbotiname Lucky Imoize,Mohammad S Obaidat,Houbing Herbert Song,Fatos Xhafa
Publisher : Elsevier
Page : 458 pages
File Size : 49,6 Mb
Release : 2024-06-10
Category : Computers
ISBN : 9780443138973

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Federated Learning for Digital Healthcare Systems by Agbotiname Lucky Imoize,Mohammad S Obaidat,Houbing Herbert Song,Fatos Xhafa Pdf

Federated Learning for Digital Healthcare Systems critically examines the key factors that contribute to the problem of applying machine learning in healthcare systems and investigates how federated learning can be employed to address the problem. The book discusses, examines, and compares the applications of federated learning solutions in emerging digital healthcare systems, providing a critical look in terms of the required resources, computational complexity, and system performance. In the first section, chapters examine how to address critical security and privacy concerns and how to revamp existing machine learning models. In subsequent chapters, the book's authors review recent advances to tackle emerging efficient and lightweight algorithms and protocols to reduce computational overheads and communication costs in wireless healthcare systems. Consideration is also given to government and economic regulations as well as legal considerations when federated learning is applied to digital healthcare systems.

Author : Lilhore, Umesh Kumar,Simaiya, Sarita,Poongodi, Manoharan,Dutt, Vishal
Publisher : IGI Global
Page : 373 pages
File Size : 53,8 Mb
Release : 2024-05-02
Category : Medical
ISBN : 9798369318751

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Federated Learning and Privacy-Preserving in Healthcare AI by Lilhore, Umesh Kumar,Simaiya, Sarita,Poongodi, Manoharan,Dutt, Vishal Pdf

The use of artificial intelligence (AI) in data-driven medicine has revolutionized healthcare, presenting practitioners with unprecedented tools for diagnosis and personalized therapy. However, this progress comes with a critical concern: the security and privacy of sensitive patient data. As healthcare increasingly leans on AI, the need for robust solutions to safeguard patient information has become more pressing than ever. Federated Learning and Privacy-Preserving in Healthcare AI emerges as the definitive solution to balancing medical progress with patient data security. This carefully curated volume not only outlines the challenges of federated learning but also provides a roadmap for implementing privacy-preserving AI systems in healthcare. By decentralizing the training of AI models, federated learning mitigates the risks associated with centralizing patient data, ensuring that critical information never leaves its original location. Aimed at healthcare professionals, AI experts, policymakers, and academics, this book not only delves into the technical aspects of federated learning but also fosters a collaborative approach to address the multifaceted challenges at the intersection of healthcare and AI.

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 53,8 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

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 : 300 pages
File Size : 55,7 Mb
Release : 2021-03-12
Category : Science
ISBN : 9780323854320

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Precision Medicine and Artificial Intelligence by Michael Mahler Pdf

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 : National Intelligence Council
Publisher : Cosimo Reports
Page : 158 pages
File Size : 45,6 Mb
Release : 2021-03
Category : Electronic
ISBN : 1646794974

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Global Trends 2040 by National Intelligence Council Pdf

"The ongoing COVID-19 pandemic marks the most significant, singular global disruption since World War II, with health, economic, political, and security implications that will ripple for years to come." -Global Trends 2040 (2021) Global Trends 2040-A More Contested World (2021), released by the US National Intelligence Council, is the latest report in its series of reports starting in 1997 about megatrends and the world's future. This report, strongly influenced by the COVID-19 pandemic, paints a bleak picture of the future and describes a contested, fragmented and turbulent world. It specifically discusses the four main trends that will shape tomorrow's world: - Demographics-by 2040, 1.4 billion people will be added mostly in Africa and South Asia. - Economics-increased government debt and concentrated economic power will escalate problems for the poor and middleclass. - Climate-a hotter world will increase water, food, and health insecurity. - Technology-the emergence of new technologies could both solve and cause problems for human life. Students of trends, policymakers, entrepreneurs, academics, journalists and anyone eager for a glimpse into the next decades, will find this report, with colored graphs, essential reading.

Author : Abdulmotaleb El Saddik,M. Shamim Hossain,Burak Kantarci
Publisher : Springer Nature
Page : 254 pages
File Size : 52,6 Mb
Release : 2019-12-03
Category : Medical
ISBN : 9783030278441

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Connected Health in Smart Cities by Abdulmotaleb El Saddik,M. Shamim Hossain,Burak Kantarci Pdf

This book reports on the theoretical foundations, fundamental applications and latest advances in various aspects of connected services for health information systems. The twelve chapters highlight state-of-the-art approaches, methodologies and systems for the design, development, deployment and innovative use of multisensory systems and tools for health management in smart city ecosystems. They exploit technologies like deep learning, artificial intelligence, augmented and virtual reality, cyber physical systems and sensor networks. Presenting the latest developments, identifying remaining challenges, and outlining future research directions for sensing, computing, communications and security aspects of connected health systems, the book will mainly appeal to academic and industrial researchers in the areas of health information systems, smart cities, and augmented reality.

Author : Pete Warden,Daniel Situnayake
Publisher : O'Reilly Media
Page : 504 pages
File Size : 54,5 Mb
Release : 2019-12-16
Category : Computers
ISBN : 9781492052012

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TinyML by Pete Warden,Daniel Situnayake Pdf

Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size

Author : Rajshree Srivastava,Nhu Gia Nguyen,Ashish Khanna,Siddhartha Bhattacharyya
Publisher : Walter de Gruyter GmbH & Co KG
Page : 180 pages
File Size : 54,7 Mb
Release : 2020-10-12
Category : Computers
ISBN : 9783110676129

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Predictive Intelligence in Biomedical and Health Informatics by Rajshree Srivastava,Nhu Gia Nguyen,Ashish Khanna,Siddhartha Bhattacharyya Pdf

Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.

Author : Xianhong Hu,Neupane, Bhanu,Echaiz, Lucia Flores,Sibal, Prateek,Rivera Lam, Macarena
Publisher : UNESCO Publishing
Page : 201 pages
File Size : 47,5 Mb
Release : 2019-11-28
Category : Electronic
ISBN : 9789231003639

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Steering AI and advanced ICTs for knowledge societies by Xianhong Hu,Neupane, Bhanu,Echaiz, Lucia Flores,Sibal, Prateek,Rivera Lam, Macarena Pdf