Download or read book Detecting Coronavirus Disease 2019 Pneumonia in Chest X Ray Images Using Deep Learning written by Ziqi Zhu and published by . This book was released on 2020 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: The coronavirus disease 2019 (COVID-19) pandemic has already become a global threat. To fight against COVID-19, effective and fast screening methods are needed. This study focuses on leveraging deep learning techniques to automatically detect COVID-19 pneumonia in chest X-ray images. Two models are trained based on transfer learning and residual neural network. The first one is a binary classifier that separates COVID-19 pneumonia and non-COVID-19 cases. It classifies all test cases correctly. The second one is a four-class classifier that distinguishes COVID-19 pneumonia, viral pneumonia, bacterial pneumonia and normal cases. It reaches an average accuracy, precision, sensitivity, specificity, and F1-score of 93\%, 93\%, 93\%, 97\%, and 93\%, respectively. To understand on how the four-class classifier detects COVID-19 pneumonia, we apply Gradient-weighted Class Activation Mapping (Grad-CAM) method and find out that the classifier is able to focus on the patchy areas in chest X-ray images and make accurate predictions.

Download or read book A Deep Transfer Learning Model with Classical Data Augmentation and CGAN to Detect COVID 19 from Chest CT Radiography Digital Images written by Mohamed Loey and published by Infinite Study. This book was released on 2020-04-16 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, five different deep convolutional neural network-based models (AlexNet, VGGNet16, VGGNet19, GoogleNet, and ResNet50) have been selected for the investigation to detect the coronavirus infected patient using chest CT radiographs digital images. The classical data augmentations along with CGAN improve the performance of classification in all selected deep transfer models. The Outcomes show that ResNet50 is the most appropriate classifier to detect the COVID-19 from chest CT dataset using the classical data augmentation and CGAN with testing accuracy of 82.91%.

Download or read book Within the Lack of Chest COVID 19 X ray Dataset A Novel Detection Model Based on GAN and Deep Transfer Learning written by Mohamed Loey and published by Infinite Study. This book was released on with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: The coronavirus (COVID-19) pandemic is putting healthcare systems across the world under unprecedented and increasing pressure according to theWorld Health Organization (WHO). With the advances in computer algorithms and especially Artificial Intelligence, the detection of this type of virus in the early stages will help in fast recovery and help in releasing the pressure off healthcare systems.

Download or read book Computational Modelling and Imaging for SARS CoV 2 and COVID 19 written by S. Prabha and published by CRC Press. This book was released on 2021-09-02 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to present new computational techniques and methodologies for the analysis of the clinical, epidemiological and public health aspects of SARS-CoV-2 and COVID-19 pandemic. The book presents the use of soft computing techniques such as machine learning algorithms for analysis of the epidemiological aspects of the SARS-CoV-2. This book clearly explains novel computational image processing algorithms for the detection of COVID-19 lesions in lung CT and X-ray images. It explores various computational methods for computerized analysis of the SARS-CoV-2 infection including severity assessment. The book provides a detailed description of the algorithms which can potentially aid in mass screening of SARS-CoV-2 infected cases. Finally the book also explains the conventional epidemiological models and machine learning techniques for the prediction of the course of the COVID-19 epidemic. It also provides real life examples through case studies. The book is intended for biomedical engineers, mathematicians, postgraduate students; researchers; medical scientists working on identifying and tracking infectious diseases.

Download or read book Medical Image Analysis written by Alejandro Frangi and published by Academic Press. This book was released on 2023-09-20 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. - An authoritative presentation of key concepts and methods from experts in the field - Sections clearly explaining key methodological principles within relevant medical applications - Self-contained chapters enable the text to be used on courses with differing structures - A representative selection of modern topics and techniques in medical image computing - Focus on medical image computing as an enabling technology to tackle unmet clinical needs - Presentation of traditional and machine learning approaches to medical image computing

Download or read book COVID 19 Prediction Decision Making and its Impacts written by K.C. Santosh and published by Springer Nature. This book was released on 2020-12-11 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to outline the issues of AI and COVID-19, involving predictions,medical support decision-making, and possible impact on human life. Starting withmajor COVID-19 issues and challenges, it takes possible AI-based solutions forseveral problems, such as public health surveillance, early (epidemic) prediction,COVID-19 positive case detection, and robotics integration against COVID-19.Beside mathematical modeling, it includes the necessity of changes in innovationsand possible COVID-19 impacts. The book covers a clear understanding of AI-driven tools and techniques, where pattern recognition, anomaly detection, machinelearning, and data analytics are considered. It aims to include the wide range ofaudiences from computer science and engineering to healthcare professionals.

Download or read book Comprehensive and Comparative Review of Covid 19 Detection Using Various Deep Learning Techniques written by Hardik Modi and published by . This book was released on 2023-12-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Academic Paper from the year 2023 in the subject Computer Science - Miscellaneous, language: English, abstract: The coronavirus disease 2019 (COVID-19), as designated by the World Health Organization, is causing a pandemic that will affect the entire world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, which is the source of COVID-19, was first identified in late December 2019 in Wuhan, China. Within a few months, the virus had spread to various countries across the world. Because COVID-19 affects millions of individuals worldwide, it has turned into a global health emergency. The most typical symptoms of COVID-19 virus are fever, a dry cough, and gastrointestinal issues. Being extremely contagious, the illness readily spreads to persons in close touch with those who are infected. Contact tracking is a good way to stop the virus from spreading, according to us. Convolutional neural networks (CNNs) in particular have achieved successful outcomes in the categorization and analysis of medical image data using artificial intelligence (AI) approaches. This survey and research proposes a deep CNN architecture for the diagnosis of COVID-19 based on the classification of chest X-ray and CT-Scan images. This review article explains how to use a database of X-ray and CT-Scan images from patients with common bacterial pneumonia to automatically diagnose coronavirus infection., proven Covid-19 infection, and common cases. The study's objective was to assess the value of COVID-19 acquisition. Globally speaking, the number of infected cases increases dramatically in the COVID-19 scenario. Because of this, medical professionals and infected patients made the crucial option to quickly embrace various medical facilities.

Download or read book Diagnosis and Analysis of COVID 19 using Artificial Intelligence and Machine Learning Based Techniques written by Mohammad Sufian Badar and published by Elsevier. This book was released on 2024-07-17 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques offers new insights and demonstrates how machine learning (ML), artificial intelligence (AI), and (Internet of Things (IoT) can be used to diagnose and fight COVID-19 infection. Sections also discuss the challenges we face in using these technologies. Chapters cover pathogenesis, transmission, diagnosis, and treatment strategies for COVID-19, Artificial Intelligence and Machine Learning, and Blockchain /IoT Blockchain technology, examining how AI can be applied as a tool for detection and containment of the spread of COVID-19, and on the socioeconomic and educational post-pandemic impacts of the disease. This is a multidisciplinary resource for those engaged in researching COVID-19 and how emerging technologies are being used as tools for detection, transmission and treatment strategies. - Describes the molecular basis of pathogenesis, epidemiology, transmission mechanism, diagnostic approaches, and the mutational landscape of SARS-CoV-2 - Provides insights into post COVID-19 symptoms and consequences - Demonstrates how machine learning, AI, and IoT is used to diagnose and fight COVID-19 infection - Examines the use of Blockchain technology/IoT and interpretation and validation of data obtained from artificial intelligence

Download or read book Artificial Intelligence for Coronavirus Outbreak written by Simon James Fong and published by Springer Nature. This book was released on 2020-06-22 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines how the wonders of AI have contributed to the battle against COVID-19. Just as history repeats itself, so do epidemics and pandemics. In the face of the novel coronavirus disease, COVID-19, the book explores whether, in this digital era where artificial intelligence is successfully applied in all areas of industry, we are doing any better than our ancestors did in dealing with pandemics. One of the most contagious diseases ever known, COVID-19 is spreading like wildfire around and has cost thousands of human lives. The book discusses how AI can help fight this deadly virus, from early warnings, prompt emergency responses, and critical decision-making to surveillance drones. Serving as a technical reference resource, data analytic tutorial and a chronicle of the application of AI in epidemics, this book will appeal to academics, students, data scientists, medical practitioners, and anybody who is concerned about this global epidemic.

Download or read book Thoracic Imaging written by Sue Copley and published by CRC Press. This book was released on 2005-04-11 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: The chest radiograph is a ubiquitous first-line investigation in many acutely ill patients and accurate interpretation is often difficult. Radiographic findings may lead to the use of more sophisticated imaging techniques such as high resolution computed tomography (HRCT), helical or spiral CT and positive emission tomography (PET).The 100 illustra

Download or read book Chest X Ray Made Easy E Book written by Jonathan Corne and published by Elsevier Health Sciences. This book was released on 2015-06-26 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This popular guide to the examination and interpretation of chest radiographs is an invaluable aid for medical students, junior doctors, nurses, physiotherapists and radiographers. Translated into over a dozen languages, this book has been widely praised for making interpretation of the chest X-ray as simple as possible The chest X-ray is often central to the diagnosis and management of a patient. As a result every doctor requires a thorough understanding of the common radiological problems. This pocketbook describes the range of conditions likely to be encountered on the wards and guides the reader through the diagnostic process based on the appearance of the abnormality shown. - Covers the full range of common radiological problems. - Includes valuable advice on how to examine an X-ray. - Assists the doctor in determining the nature of the abnormality. - Points the clinician towards a possible differential diagnosis. - A larger page size allows for larger and clearer illustrations. - A new chapter on the sick patient covers the patient on ITU and the appearance of lines and tubes. - There is extended use of CT imaging with advice on choosing modalities depending on the clinical circumstances. - A new section of chest x-ray problems incorporates particularly challenging case histories. - The international relevance of the text has been expanded with additional text and images.

Download or read book 2009 IEEE Conference on Computer Vision and Pattern Recognition written by IEEE Staff and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Shape Contour and Grouping in Computer Vision written by David A. Forsyth and published by Springer Science & Business Media. This book was released on 1999-11-03 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision has been successful in several important applications recently. Vision techniques can now be used to build very good models of buildings from pictures quickly and easily, to overlay operation planning data on a neuros- geon’s view of a patient, and to recognise some of the gestures a user makes to a computer. Object recognition remains a very di cult problem, however. The key questions to understand in recognition seem to be: (1) how objects should be represented and (2) how to manage the line of reasoning that stretches from image data to object identity. An important part of the process of recognition { perhaps, almost all of it { involves assembling bits of image information into helpful groups. There is a wide variety of possible criteria by which these groups could be established { a set of edge points that has a symmetry could be one useful group; others might be a collection of pixels shaded in a particular way, or a set of pixels with coherent colour or texture. Discussing this process of grouping requires a detailed understanding of the relationship between what is seen in the image and what is actually out there in the world.

Download or read book Deep Learning for Internet of Things Infrastructure written by Uttam Ghosh and published by CRC Press. This book was released on 2021-09-30 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users. FEATURES Promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructures Addresses emerging trends and issues on IoT systems and services across various application domains Investigates the challenges posed by the implementation of deep learning on IoT networking models and services Provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT Explores new functions and technologies to provide adaptive services and intelligent applications for different end users Uttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.

Download or read book Diagnostic Imaging of Novel Coronavirus Pneumonia written by Minming Zhang and published by Springer Nature. This book was released on 2020-09-19 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents radiological findings in patients with 2019 Novel Coronavirus Pneumonia (COVID-19). It starts with a general review of COVID-19 Pneumonia discovery, including etiology characteristics, transmission routes and pathogenic mechanisms. In the following chapters, details in clinical classification, imaging manifestations in different groups, and imaging features of family aggregated coronavirus pneumonia are introduced. In addition, key points in differential diagnosis of COVID-19 Pneumonia are summarized in the last chapter. The book provides a valuable reference source for radiologists and doctors working in the area of COVID-19 Pneumonia.

Download or read book Intelligence Based Medicine written by Anthony C. Chang and published by Academic Press. This book was released on 2020-06-27 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. - Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything - Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists - Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future - Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare

Download or read book Computational Intelligence and Healthcare Informatics written by Om Prakash Jena and published by John Wiley & Sons. This book was released on 2021-10-19 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: COMPUTATIONAL INTELLIGENCE and HEALTHCARE INFORMATICS The book provides the state-of-the-art innovation, research, design, and implements methodological and algorithmic solutions to data processing problems, designing and analysing evolving trends in health informatics, intelligent disease prediction, and computer-aided diagnosis. Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. With the rapid advance of technology, artificial intelligence (AI) techniques are being effectively used in the fields of health to improve the efficiency of treatments, avoid the risk of false diagnoses, make therapeutic decisions, and predict the outcome in many clinical scenarios. Modern health treatments are faced with the challenge of acquiring, analyzing and applying the large amount of knowledge necessary to solve complex problems. Computational intelligence in healthcare mainly uses computer techniques to perform clinical diagnoses and suggest treatments. In the present scenario of computing, CI tools present adaptive mechanisms that permit the understanding of data in difficult and changing environments. The desired results of CI technologies profit medical fields by assembling patients with the same types of diseases or fitness problems so that healthcare facilities can provide effectual treatments. This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with it. Contained in this book are state-of-the-art methods of computational intelligence and other allied techniques used in the healthcare system, as well as advances in different CI methods that will confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide researchers with a platform encompassing state-of-the-art innovations; research and design; implementation of methodological and algorithmic solutions to data processing problems; and the design and analysis of evolving trends in health informatics, intelligent disease prediction and computer-aided diagnosis. Audience The book is of interest to artificial intelligence and biomedical scientists, researchers, engineers and students in various settings such as pharmaceutical & biotechnology companies, virtual assistants developing companies, medical imaging & diagnostics centers, wearable device designers, healthcare assistance robot manufacturers, precision medicine testers, hospital management, and researchers working in healthcare system.