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Deep Learning For Covid Image Analysis

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Deep Learning for COVID Image Analysis

Deep Learning for COVID Image Analysis Book
Author : Hayit Greenspan,S. Kevin Zhou
Publisher : Academic Press
Release : 2021-10-15
ISBN : 9780323901079
Language : En, Es, Fr & De

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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

Artificial Intelligence and Machine Learning for COVID 19

Artificial Intelligence and Machine Learning for COVID 19 Book
Author : Fadi Al-Turjman
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 3030601889
Language : En, Es, Fr & De

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Book Description :

Download Artificial Intelligence and Machine Learning for COVID 19 book written by Fadi Al-Turjman, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Thoracic Image Analysis

Thoracic Image Analysis Book
Author : Jens Petersen
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 3030624692
Language : En, Es, Fr & De

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Book Description :

Download Thoracic Image Analysis book written by Jens Petersen, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Computer Vision and Image Processing

Computer Vision and Image Processing Book
Author : Satish Kumar Singh
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 981161086X
Language : En, Es, Fr & De

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Book Description :

Download Computer Vision and Image Processing book written by Satish Kumar Singh, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Deep Learning for Medical Decision Support Systems

Deep Learning for Medical Decision Support Systems Book
Author : Utku Kose,Omer Deperlioglu,Jafar Alzubi,Bogdan Patrut
Publisher : Springer Nature
Release : 2020-06-17
ISBN : 981156325X
Language : En, Es, Fr & De

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Book Description :

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.

AI Powered IoT for COVID 19

AI Powered IoT for COVID 19 Book
Author : Fadi Al-Turjman
Publisher : CRC Press
Release : 2020-12-10
ISBN : 1000298000
Language : En, Es, Fr & De

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Book Description :

The Internet of Things (IoT) has made revolutionary advances in the utility grid as we know it. Among these advances, intelligent medical services are gaining much interest. The use of Artificial Intelligence (AI) is increasing day after day in fighting one of the most significant viruses, COVID-19. The purpose of this book is to present the detailed recent exploration of AI and IoT in the COVID-19 pandemic and similar applications. The integrated AI and IoT paradigm is widely used in most medical applications, as well as in sectors that deal with transacting data every day. This book can be used by computer science undergraduate and postgraduate students; researchers and practitioners; and city administrators, policy makers, and government regulators. It presents a smart and up-to-date model for COVID-19 and similar applications. Novel architectural and medical use cases in the smart city project are the core aspects of this book. The wide variety of topics it presents offers readers multiple perspectives on a variety of disciplines. Prof. Dr. Fadi Al-Turjman received his PhD in computer science from Queen’s University, Kingston, Ontario, Canada, in 2011. He is a full professor and research center director at Near East University, Nicosia, Cyprus.

Machine Learning Image Processing Network Security and Data Sciences

Machine Learning  Image Processing  Network Security and Data Sciences Book
Author : Arup Bhattacharjee
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 9811563152
Language : En, Es, Fr & De

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Book Description :

Download Machine Learning Image Processing Network Security and Data Sciences book written by Arup Bhattacharjee, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Intelligent Systems and Methods to Combat Covid 19

Intelligent Systems and Methods to Combat Covid 19 Book
Author : Amit Joshi
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 9811565724
Language : En, Es, Fr & De

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Book Description :

Download Intelligent Systems and Methods to Combat Covid 19 book written by Amit Joshi, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Advanced Computing

Advanced Computing Book
Author : Deepak Garg
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 9811604010
Language : En, Es, Fr & De

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Book Description :

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Proceedings of the Future Technologies Conference FTC 2020 Volume 1

Proceedings of the Future Technologies Conference  FTC  2020  Volume 1 Book
Author : Kohei Arai,Supriya Kapoor,Rahul Bhatia
Publisher : Springer Nature
Release : 2021
ISBN : 3030631281
Language : En, Es, Fr & De

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Book Description :

This book provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research. The fifth 2020 Future Technologies Conference was organized virtually and received a total of 590 submissions from academic pioneering researchers, scientists, industrial engineers, and students from all over the world. The submitted papers covered a wide range of important topics including but not limited to computing, electronics, artificial intelligence, robotics, security and communications and their applications to the real world. After a double-blind peer review process, 210 submissions (including 6 poster papers) have been selected to be included in these proceedings. One of the meaningful and valuable dimensions of this conference is the way it brings together a large group of technology geniuses in one venue to not only present breakthrough research in future technologies, but also to promote discussions and debate of relevant issues, challenges, opportunities and research findings. The authors hope that readers find the book interesting, exciting and inspiring.

Proceedings of International Conference on Computational Intelligence and Data Engineering

Proceedings of International Conference on Computational Intelligence and Data Engineering Book
Author : Nabendu Chaki,Jerzy Pejas,Nagaraju Devarakonda,Ram Mohan Rao Kovvur
Publisher : Springer Nature
Release : 2020-12-20
ISBN : 9811587671
Language : En, Es, Fr & De

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Book Description :

This book is a collection of high-quality research work on cutting-edge technologies and the most-happening areas of computational intelligence and data engineering. It includes selected papers from the International Conference on Computational Intelligence and Data Engineering (ICCIDE 2020). It covers various topics, including collective intelligence, intelligent transportation systems, fuzzy systems, Bayesian network, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence and speech processing.

Pattern Recognition ICPR International Workshops and Challenges

Pattern Recognition  ICPR International Workshops and Challenges Book
Author : Alberto Del Bimbo
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 3030687996
Language : En, Es, Fr & De

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Book Description :

Download Pattern Recognition ICPR International Workshops and Challenges book written by Alberto Del Bimbo, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Machine Learning in Medical Imaging

Machine Learning in Medical Imaging Book
Author : Mingxia Liu
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 3030598616
Language : En, Es, Fr & De

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Book Description :

Download Machine Learning in Medical Imaging book written by Mingxia Liu, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Artificial Neural Networks and Machine Learning ICANN 2020

Artificial Neural Networks and Machine Learning     ICANN 2020 Book
Author : Igor Farkaš
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 3030616096
Language : En, Es, Fr & De

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Book Description :

Download Artificial Neural Networks and Machine Learning ICANN 2020 book written by Igor Farkaš, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Artificial Intelligence and Soft Computing

Artificial Intelligence and Soft Computing Book
Author : Leszek Rutkowski
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 3030615340
Language : En, Es, Fr & De

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Book Description :

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Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence Book
Author : A.J. Tallón-Ballesteros,C.-H. Chen
Publisher : IOS Press
Release : 2020-12-15
ISBN : 1643681370
Language : En, Es, Fr & De

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Book Description :

Machine learning and artificial intelligence are already widely applied to facilitate our daily lives, as well as scientific research, but with the world currently facing a global COVID-19 pandemic, their capacity to provide an important tool to support those searching for a way to combat the novel corona virus has never been more important. This book presents the proceedings of the International Conference on Machine Learning and Intelligent Systems (MLIS 2020), which was due to be held in Seoul, Korea, from 25-28 October 2020, but which was delivered as an online conference on the same dates due to COVID-19 restrictions. MLIS 2020 was the latest in a series of annual conferences that aim to provide a platform for exchanging knowledge about the most recent scientific and technological advances in the field of machine learning and intelligent systems. The annual conference also strengthens links within the scientific community in related research areas. The book contains 53 papers, selected from more than 160 submissions and presented at MLIS 2020. Selection was based on the results of review and scored on: originality, scientific/practical significance, compelling logical reasoning and language. Topics covered include: data mining, image processing, neural networks, human health, natural language processing, video processing, computational intelligence, expert systems, human-computer interaction, deep learning, and robotics. Offering a current overview of research and developments in machine learning and artificial intelligence, the book will be of interest to all those working in the field.

Handbook of Deep Learning in Biomedical Engineering and Health Informatics

Handbook of Deep Learning in Biomedical Engineering and Health Informatics Book
Author : E Golden Julie,Y Harold Robinson,S M Jaisakthi
Publisher : Apple Academic Press
Release : 2021-08
ISBN : 9781771889988
Language : En, Es, Fr & De

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Book Description :

This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat the patients more effectively. Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. The volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc. Key features: Introduces important recent technological advancements in the field Describes the various techniques, platforms, and tools used in biomedical deep learning systems Includes informative case studies that help to explain the new technologies Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.

Data Stream Mining Processing

Data Stream Mining   Processing Book
Author : Sergii Babichev
Publisher : Springer Nature
Release : 2021-04-16
ISBN : 3030616568
Language : En, Es, Fr & De

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Book Description :

Download Data Stream Mining Processing book written by Sergii Babichev, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Advances in Visual Computing

Advances in Visual Computing Book
Author : George Bebis,Zhaozheng Yin,Edward Kim,Jan Bender,Kartic Subr,Bum Chul Kwon,Jian Zhao,Denis Kalkofen,George Baciu
Publisher : Springer Nature
Release : 2020-12-11
ISBN : 3030645592
Language : En, Es, Fr & De

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Book Description :

This two-volume set of LNCS 12509 and 12510 constitutes the refereed proceedings of the 15th International Symposium on Visual Computing, ISVC 2020, which was supposed to be held in San Diego, CA, USA in October 2020, took place virtually instead due to the COVID-19 pandemic. The 118 papers presented in these volumes were carefully reviewed and selected from 175 submissions. The papers are organized into the following topical sections: Part I: deep learning; segmentation; visualization; video analysis and event recognition; ST: computational bioimaging; applications; biometrics; motion and tracking; computer graphics; virtual reality; and ST: computer vision advances in geo-spatial applications and remote sensing Part II: object recognition/detection/categorization; 3D reconstruction; medical image analysis; vision for robotics; statistical pattern recognition; posters

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro oncology

Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro oncology Book
Author : Seyed Mostafa Kia,Hassan Mohy-ud-Din,Ahmed Abdulkadir,Cher Bass,Mohamad Habes,Jane Maryam Rondina,Chantal Tax,Hongzhi Wang,Thomas Wolfers,Saima Rathore,Madhura Ingalhalikar
Publisher : Springer Nature
Release : 2020-12-30
ISBN : 3030668436
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.* For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.