Meta Learning With Medical Imaging And Health Informatics Applications

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Meta Learning With Medical Imaging and Health Informatics Applications

Author : Hien Van Nguyen
Publisher : Academic Press
ISBN 13 : 0323998526
Total Pages : 430 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Meta Learning With Medical Imaging and Health Informatics Applications by : Hien Van Nguyen

Download or read book Meta Learning With Medical Imaging and Health Informatics Applications written by Hien Van Nguyen and published by Academic Press. This book was released on 2022-09-24 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks’ fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks. This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions. First book on applying Meta Learning to medical imaging Pioneers in the field as contributing authors to explain the theory and its development Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly

Meta-Learning Frameworks for Imaging Applications

Author : Sharma, Ashok
Publisher : IGI Global
ISBN 13 : 1668476614
Total Pages : 271 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Meta-Learning Frameworks for Imaging Applications by : Sharma, Ashok

Download or read book Meta-Learning Frameworks for Imaging Applications written by Sharma, Ashok and published by IGI Global. This book was released on 2023-09-28 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-learning, or learning to learn, has been gaining popularity in recent years to adapt to new tasks systematically and efficiently in machine learning. In the book, Meta-Learning Frameworks for Imaging Applications, experts from the fields of machine learning and imaging come together to explore the current state of meta-learning and its application to medical imaging and health informatics. The book presents an overview of the meta-learning framework, including common versions such as model-agnostic learning, memory augmentation, prototype networks, and learning to optimize. It also discusses how meta-learning can be applied to address fundamental limitations of deep neural networks, such as high data demand, computationally expensive training, and limited ability for task transfer. One critical topic in imaging is image segmentation, and the book explores how a meta-learning-based framework can help identify the best image segmentation algorithm, which would be particularly beneficial in the healthcare domain. This book is relevant to healthcare institutes, e-commerce companies, and educational institutions, as well as professionals and practitioners in the intelligent system, computational data science, network applications, and biomedical applications fields. It is also useful for domain developers and project managers from diagnostic and pharmacy companies involved in the development of medical expert systems. Additionally, graduate and master students in intelligent systems, big data management, computational intelligent approaches, computer vision, and biomedical science can use this book for their final projects and specific courses.

Medical Imaging and Health Informatics

Author : Tushar H. Jaware
Publisher : John Wiley & Sons
ISBN 13 : 1119819148
Total Pages : 388 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Medical Imaging and Health Informatics by : Tushar H. Jaware

Download or read book Medical Imaging and Health Informatics written by Tushar H. Jaware and published by John Wiley & Sons. This book was released on 2022-05-26 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: MEDICAL IMAGING AND HEALTH INFORMATICS Provides a comprehensive review of artificial intelligence (AI) in medical imaging as well as practical recommendations for the usage of machine learning (ML) and deep learning (DL) techniques for clinical applications. Medical imaging and health informatics is a subfield of science and engineering which applies informatics to medicine and includes the study of design, development, and application of computational innovations to improve healthcare. The health domain has a wide range of challenges that can be addressed using computational approaches; therefore, the use of AI and associated technologies is becoming more common in society and healthcare. Currently, deep learning algorithms are a promising option for automated disease detection with high accuracy. Clinical data analysis employing these deep learning algorithms allows physicians to detect diseases earlier and treat patients more efficiently. Since these technologies have the potential to transform many aspects of patient care, disease detection, disease progression and pharmaceutical organization, approaches such as deep learning algorithms, convolutional neural networks, and image processing techniques are explored in this book. This book also delves into a wide range of image segmentation, classification, registration, computer-aided analysis applications, methodologies, algorithms, platforms, and tools; and gives a holistic approach to the application of AI in healthcare through case studies and innovative applications. It also shows how image processing, machine learning and deep learning techniques can be applied for medical diagnostics in several specific health scenarios such as COVID-19, lung cancer, cardiovascular diseases, breast cancer, liver tumor, bone fractures, etc. Also highlighted are the significant issues and concerns regarding the use of AI in healthcare together with other allied areas, such as the Internet of Things (IoT) and medical informatics, to construct a global multidisciplinary forum. Audience The core audience comprises researchers and industry engineers, scientists, radiologists, healthcare professionals, data scientists who work in health informatics, computer vision and medical image analysis.

Deep Learning in Biomedical and Health Informatics

Author : M. A. Jabbar
Publisher : CRC Press
ISBN 13 : 1000429121
Total Pages : 251 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Deep Learning in Biomedical and Health Informatics by : M. A. Jabbar

Download or read book Deep Learning in Biomedical and Health Informatics written by M. A. Jabbar and published by CRC Press. This book was released on 2021-09-27 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a proficient guide on the relationship between Artificial Intelligence (AI) and healthcare and how AI is changing all aspects of the healthcare industry. It also covers how deep learning will help in diagnosis and the prediction of disease spread. The editors present a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing, and highlights various challenges in applying deep learning in health care. This book also includes applications and case studies across all areas of AI in healthcare data. The editors also aim to provide new theories, techniques, developments, and applications of deep learning, and to solve emerging problems in healthcare and other domains. This book is intended for computer scientists, biomedical engineers, and healthcare professionals researching and developing deep learning techniques. In short, the volume : Discusses the relationship between AI and healthcare, and how AI is changing the health care industry. Considers uses of deep learning in diagnosis and prediction of disease spread. Presents a comprehensive review of research applying deep learning in health informatics across multiple fields. Highlights challenges in applying deep learning in the field. Promotes research in ddeep llearning application in understanding the biomedical process. Dr.. M.A. Jabbar is a professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India. Prof. (Dr.) Ajith Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA. Dr.. Onur Dogan is an assistant professor at İzmir Bakırçay University, Turkey. Prof. Dr. Ana Madureira is the Director of The Interdisciplinary Studies Research Center at Instituto Superior de Engenharia do Porto (ISEP), Portugal. Dr.. Sanju Tiwari is a senior researcher at Universidad Autonoma de Tamaulipas, Mexico.

Deep Learning for Medical Image Analysis

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 0323858880
Total Pages : 544 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou

Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-12-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. · Covers common research problems in medical image analysis and their challenges · Describes the latest deep learning methods and the theories behind approaches for medical image analysis · Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache

Medical Image Analysis

Author : Alejandro Frangi
Publisher : Academic Press
ISBN 13 : 0128136588
Total Pages : 700 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Medical Image Analysis by : Alejandro Frangi

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. Provides an authoritative description of key concepts and methods Includes tutorial-based sections that clearly explain principles and their application to different medical domains Presents a representative selection of topics to match a modern and relevant approach to medical image computing

Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology

Author : Seyed-Ahmad Ahmadi
Publisher : Springer Nature
ISBN 13 : 3031550889
Total Pages : 184 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology by : Seyed-Ahmad Ahmadi

Download or read book Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology written by Seyed-Ahmad Ahmadi and published by Springer Nature. This book was released on 2024 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This LNCS conference volume constitutes the proceedings of the MICCAI Workshop GRAIL 2023 and MICCAI Challenge OCELOT 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, September 23, and October 4, 2023. The 9 full papers (GRAIL 2023) and 6 full papers (OCELOT 2023) included in this volume were carefully reviewed and selected from GRAIL 14 (GRAIL 2023) and 6 (OCELOT 2023) submissions. The conference GRAIL 2023 a wide set of methods and application and OCELOT 2023 focuses on the cover a wide range of methods utilizing tissue information for better cell detection, in the sense of training strategy, model architecture, and especially how to model cell-tissue relationships.

Micro-Electronics and Telecommunication Engineering

Author : Devendra Kumar Sharma
Publisher : Springer Nature
ISBN 13 : 9819995620
Total Pages : 813 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Micro-Electronics and Telecommunication Engineering by : Devendra Kumar Sharma

Download or read book Micro-Electronics and Telecommunication Engineering written by Devendra Kumar Sharma and published by Springer Nature. This book was released on 2024 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zusammenfassung: The book presents high-quality papers from the Seventh International Conference on Microelectronics and Telecommunication Engineering (ICMETE 2023). It discusses the latest technological trends and advances in major research areas such as microelectronics, wireless communications, optical communication, signal processing, image processing, Big Data, cloud computing, artificial intelligence, and sensor network applications. This book includes the contributions of national/international scientists, researchers, and engineers from both academia and the industry. The contents of this book will be useful to researchers, professionals, and students alike

Practical Imaging Informatics

Author : Barton F. Branstetter IV
Publisher : Springer Nature
ISBN 13 : 1071617567
Total Pages : 664 pages
Book Rating : 4.0/5 (716 download)

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Book Synopsis Practical Imaging Informatics by : Barton F. Branstetter IV

Download or read book Practical Imaging Informatics written by Barton F. Branstetter IV and published by Springer Nature. This book was released on 2021-11-02 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition is a comprehensive source of imaging informatics fundamentals and how those fundamentals are applied in everyday practice. Imaging Informatics Professionals (IIPs) play a critical role in healthcare, and the scope of the profession has grown far beyond the boundaries of the PACS. A successful IIP must understand the PACS itself and all the software systems networked together in the medical environment. Additionally, an IIP must know the workflows of all the imaging team members, have a base in several medical specialties and be fully capable in the realm of information technology. Practical Imaging Informatics has been reorganized to follow a logical progression from basic background information on IT and clinical image management, through daily operations and troubleshooting, to long-term planning. The book has been fully updated to include the latest technologies and procedures, including artificial intelligence and machine learning. Written by a team of renowned international authors from the Society for Imaging Informatics in Medicine and the European Society of Medical Imaging Informatics, this book is an indispensable reference for the practicing IIP. In addition, it is an ideal guide for those studying for a certification exam, biomedical informaticians, trainees with an interest in informatics, and any professional who needs quick access to the nuts and bolts of imaging informatics.

Deep Learning Techniques for Biomedical and Health Informatics

Author : Basant Agarwal
Publisher : Academic Press
ISBN 13 : 0128190620
Total Pages : 367 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Deep Learning Techniques for Biomedical and Health Informatics by : Basant Agarwal

Download or read book Deep Learning Techniques for Biomedical and Health Informatics written by Basant Agarwal and published by Academic Press. This book was released on 2020-01-14 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

Author : Om Prakash Jena
Publisher : CRC Press
ISBN 13 : 1000533972
Total Pages : 332 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications by : Om Prakash Jena

Download or read book Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications written by Om Prakash Jena and published by CRC Press. This book was released on 2022-02-25 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments. This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems. Features: Covers the fundamentals of ML and DL in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in ML/DL models Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios. Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India. Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.

Deep Learning for Medical Image Analysis

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 0128104090
Total Pages : 458 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou

Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2017-01-18 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Applied Smart Health Care Informatics

Author : Sourav De
Publisher : John Wiley & Sons
ISBN 13 : 1119742986
Total Pages : 228 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Applied Smart Health Care Informatics by : Sourav De

Download or read book Applied Smart Health Care Informatics written by Sourav De and published by John Wiley & Sons. This book was released on 2022-02-23 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new research directions and highlight the smart technologies that are central to establishing proactive health management, supporting enhanced coordination of care, and improving the overall quality of healthcare services. Provides an overview of different deep learning applications for intelligent healthcare informatics management Describes novel methodologies and emerging trends in artificial intelligence and computational intelligence and their relevance to health information engineering and management Proposes IoT solutions that disseminate essential medical information for intelligent healthcare management Discusses mobile-based healthcare management, content-based image retrieval, and computer-aided diagnosis using machine and deep learning techniques Examines the use of exploratory data analysis in intelligent healthcare informatics systems Applied Smart Health Care Informatics: A Computational Intelligence Perspective is an invaluable text for graduate students, postdoctoral researchers, academic lecturers, and industry professionals working in the area of healthcare and intelligent soft computing.

Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

Author : Le Lu
Publisher : Springer Nature
ISBN 13 : 3030139697
Total Pages : 461 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics by : Le Lu

Download or read book Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics written by Le Lu and published by Springer Nature. This book was released on 2019-09-19 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book’s chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval. The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

Deep Learning Applications in Medical Imaging

Author : Saxena, Sanjay
Publisher : IGI Global
ISBN 13 : 1799850722
Total Pages : 274 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Learning Applications in Medical Imaging by : Saxena, Sanjay

Download or read book Deep Learning Applications in Medical Imaging written by Saxena, Sanjay and published by IGI Global. This book was released on 2020-10-16 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

Machine Learning and Analytics in Healthcare Systems

Author : Himani Bansal
Publisher : CRC Press
ISBN 13 : 1000406199
Total Pages : 275 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning and Analytics in Healthcare Systems by : Himani Bansal

Download or read book Machine Learning and Analytics in Healthcare Systems written by Himani Bansal and published by CRC Press. This book was released on 2021-06-30 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridges the gap between engineering and medicine in combining the design and problem solving skills of engineering with health sciences Explores real-world case studies in machine learning and healthcare analytics Presents a detailed exploration of applications of machine learning in healthcare systems Provides readers with how the industry avoids some of the consequences of old methods of data sharing strategies Offers readers multiple perspectives on a variety of disciplines

Approaches and Applications of Deep Learning in Virtual Medical Care

Author : Zaman, Noor
Publisher : IGI Global
ISBN 13 : 1799889300
Total Pages : 293 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Approaches and Applications of Deep Learning in Virtual Medical Care by : Zaman, Noor

Download or read book Approaches and Applications of Deep Learning in Virtual Medical Care written by Zaman, Noor and published by IGI Global. This book was released on 2022-02-25 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent advancements in the machine learning paradigm have various applications, specifically in the field of medical data analysis. Research has proven the high accuracy of deep learning algorithms, and they have become a standard choice for analyzing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Approaches and Applications of Deep Learning in Virtual Medical Care considers the applications of deep learning in virtual medical care and delves into complex deep learning algorithms, calibrates models, and improves the predictions of the trained model on medical imaging. Covering topics such as big data and medical sensors, this critical reference source is ideal for researchers, academicians, practitioners, industry professionals, hospital workers, scholars, instructors, and students.