Computational Analysis And Deep Learning For Medical Care

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Computational Analysis and Deep Learning for Medical Care

Amit Kumar Tyagi
Computational Analysis and Deep Learning for Medical Care Book PDF

Author : Amit Kumar Tyagi
Publisher : John Wiley & Sons
Page : 532 pages
File Size : 42,8 Mb
Release : 2021-08-10
Category : Computers
ISBN : 9781119785736

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Computational Analysis and Deep Learning for Medical Care by Amit Kumar Tyagi Pdf

The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.

Computational Intelligence for Machine Learning and Healthcare Informatics

Rajshree Srivastava,Pradeep Kumar Mallick,Siddharth Swarup Rautaray,Manjusha Pandey
Computational Intelligence for Machine Learning and Healthcare Informatics Book PDF

Author : Rajshree Srivastava,Pradeep Kumar Mallick,Siddharth Swarup Rautaray,Manjusha Pandey
Publisher : Walter de Gruyter GmbH & Co KG
Page : 346 pages
File Size : 51,9 Mb
Release : 2020-06-22
Category : Computers
ISBN : 9783110648195

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Computational Intelligence for Machine Learning and Healthcare Informatics by Rajshree Srivastava,Pradeep Kumar Mallick,Siddharth Swarup Rautaray,Manjusha Pandey Pdf

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

Computational Analysis and Deep Learning for Medical Care

Amit Kumar Tyagi
Computational Analysis and Deep Learning for Medical Care Book PDF

Author : Amit Kumar Tyagi
Publisher : John Wiley & Sons
Page : 532 pages
File Size : 52,8 Mb
Release : 2021-08-24
Category : Computers
ISBN : 9781119785729

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Computational Analysis and Deep Learning for Medical Care by Amit Kumar Tyagi Pdf

The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.

Deep Learning for Medical Image Analysis

S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Deep Learning for Medical Image Analysis Book PDF

Author : S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Publisher : Academic Press
Page : 0 pages
File Size : 40,7 Mb
Release : 2023-10-01
Category : Computers
ISBN : 032385124X

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Deep Learning for Medical Image Analysis by S. Kevin Zhou,Hayit Greenspan,Dinggang Shen Pdf

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.

Deep Learning and Convolutional Neural Networks for Medical Image Computing

Le Lu,Yefeng Zheng,Gustavo Carneiro,Lin Yang
Deep Learning and Convolutional Neural Networks for Medical Image Computing Book PDF

Author : Le Lu,Yefeng Zheng,Gustavo Carneiro,Lin Yang
Publisher : Springer
Page : 326 pages
File Size : 44,9 Mb
Release : 2017-07-12
Category : Computers
ISBN : 9783319429991

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Deep Learning and Convolutional Neural Networks for Medical Image Computing by Le Lu,Yefeng Zheng,Gustavo Carneiro,Lin Yang Pdf

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Deep Learning in Healthcare

Yen-Wei Chen,Lakhmi C. Jain
Deep Learning in Healthcare Book PDF

Author : Yen-Wei Chen,Lakhmi C. Jain
Publisher : Springer Nature
Page : 225 pages
File Size : 44,6 Mb
Release : 2019-11-18
Category : Technology & Engineering
ISBN : 9783030326067

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Deep Learning in Healthcare by Yen-Wei Chen,Lakhmi C. Jain Pdf

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.

Deep Learning for Medical Applications with Unique Data

Deepak Gupta,Utku Kose,Ashish Khanna,Valentina Emilia Balas
Deep Learning for Medical Applications with Unique Data Book PDF

Author : Deepak Gupta,Utku Kose,Ashish Khanna,Valentina Emilia Balas
Publisher : Academic Press
Page : 258 pages
File Size : 47,7 Mb
Release : 2022-02-15
Category : Science
ISBN : 9780128241462

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Deep Learning for Medical Applications with Unique Data by Deepak Gupta,Utku Kose,Ashish Khanna,Valentina Emilia Balas Pdf

Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The volume discusses not only positive findings, but also negative ones obtained by deep learning techniques, including the use of newly developed deep learning techniques rarely reported in the existing literature. The book excludes research works with ready data sets and includes only unique data use to better understand the state of deep learning in real-world cases, along with the feedback and user experiences from physicians and medical staff for applied deep learning-based solutions. Other applications presented in the book include hybrid solutions with deep learning support, disease diagnosis with deep learning focusing on rare diseases and cancer, patient care and treatment, genomics research, as well as research on robotics and autonomous systems. Introduces deep learning, demonstrating concepts for a wide variety of medical applications using unique data, excluding research with ready datasets Encompasses a wide variety of biomedical applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing and disease diagnosis Provides a robust set of methods that will help readers appropriately and judiciously use the most suitable deep learning techniques for their applications

Computational Intelligence and Healthcare Informatics

Om Prakash Jena,Alok Ranjan Tripathy,Ahmed A. Elngar,Zdzislaw Polkowski
Computational Intelligence and Healthcare Informatics Book PDF

Author : Om Prakash Jena,Alok Ranjan Tripathy,Ahmed A. Elngar,Zdzislaw Polkowski
Publisher : John Wiley & Sons
Page : 434 pages
File Size : 55,5 Mb
Release : 2021-10-19
Category : Computers
ISBN : 9781119818687

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Computational Intelligence and Healthcare Informatics by Om Prakash Jena,Alok Ranjan Tripathy,Ahmed A. Elngar,Zdzislaw Polkowski Pdf

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.

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

Om Prakash Jena,Bharat Bhushan,Utku Kose
Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications Book PDF

Author : Om Prakash Jena,Bharat Bhushan,Utku Kose
Publisher : CRC Press
Page : 332 pages
File Size : 53,8 Mb
Release : 2022-02-25
Category : Computers
ISBN : 9781000533972

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Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications by Om Prakash Jena,Bharat Bhushan,Utku Kose Pdf

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 in Medical Image Analysis

Gobert Lee,Hiroshi Fujita
Deep Learning in Medical Image Analysis Book PDF

Author : Gobert Lee,Hiroshi Fujita
Publisher : Springer Nature
Page : 184 pages
File Size : 49,5 Mb
Release : 2020-02-06
Category : Medical
ISBN : 9783030331283

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Deep Learning in Medical Image Analysis by Gobert Lee,Hiroshi Fujita Pdf

This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics

Pradeep N,Sandeep Kautish,Sheng-Lung Peng
Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics Book PDF

Author : Pradeep N,Sandeep Kautish,Sheng-Lung Peng
Publisher : Academic Press
Page : 374 pages
File Size : 52,7 Mb
Release : 2021-06-10
Category : Science
ISBN : 9780128220443

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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics by Pradeep N,Sandeep Kautish,Sheng-Lung Peng Pdf

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

Om Prakash Jena,Bharat Bhushan,Nitin Rakesh,Parma Nand Astya,Yousef Farhaoui
Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems Book PDF

Author : Om Prakash Jena,Bharat Bhushan,Nitin Rakesh,Parma Nand Astya,Yousef Farhaoui
Publisher : CRC Press
Page : 321 pages
File Size : 54,6 Mb
Release : 2022-05-18
Category : Computers
ISBN : 9781000486827

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Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems by Om Prakash Jena,Bharat Bhushan,Nitin Rakesh,Parma Nand Astya,Yousef Farhaoui Pdf

The goal of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and have led to the modern age of machine learning, deep learning and Internet of Medical Things (IoMT) with their proliferation, mobility and agility. This book exposes different dimensions of applications for computational intelligence and explains its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to ensure high-quality data processing, medical image and signal analysis and improved healthcare applications. This book also explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems. Furthermore, it provides the healthcare sector with innovative advances in theory, analytical approaches, numerical simulation, statistical analysis, modelling, advanced deployment, case studies, analytical results, computational structuring and significant progress in the field of machine learning and deep learning in healthcare applications. FEATURES Explores different dimensions of computational intelligence applications and illustrates its use in the solution of assorted real-world biomedical and healthcare problems Provides guidance in developing intelligence-based diagnostic systems, efficient models and cost-effective machines Provides the latest research findings, solutions to the concerning issues and relevant theoretical frameworks in the area of machine learning and deep learning for healthcare systems Describes experiences and findings relating to protocol design, prototyping, experimental evaluation, real testbeds and empirical characterization of security and privacy interoperability issues in healthcare applications Explores and illustrates the current and future impacts of pandemics and mitigates risk in healthcare with advanced analytics This book is intended for students, researchers, professionals and policy makers working in the fields of public health and in the healthcare sector. Scientists and IT specialists will also find this book beneficial for research exposure and new ideas in the field of machine learning and deep learning.

Applied Smart Health Care Informatics

Sourav De,Rik Das,Siddhartha Bhattacharyya,Ujjwal Maulik
Applied Smart Health Care Informatics Book PDF

Author : Sourav De,Rik Das,Siddhartha Bhattacharyya,Ujjwal Maulik
Publisher : John Wiley & Sons
Page : 228 pages
File Size : 55,7 Mb
Release : 2022-03-07
Category : Technology & Engineering
ISBN : 9781119743170

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Applied Smart Health Care Informatics by Sourav De,Rik Das,Siddhartha Bhattacharyya,Ujjwal Maulik Pdf

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.

Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems

Parvathaneni Naga Srinivasu
Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems Book PDF

Author : Parvathaneni Naga Srinivasu
Publisher : Bentham Science Publishers
Page : 225 pages
File Size : 50,7 Mb
Release : 2022-10-05
Category : Technology & Engineering
ISBN : 9781681089577

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Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems by Parvathaneni Naga Srinivasu Pdf

Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems explains the emerging technology that currently drives computer-aided diagnosis, medical analysis and other electronic healthcare systems. 11 book chapters cover advances in biomedical engineering fields achieved through deep learning and soft-computing techniques. Readers are given a fresh perspective on the impact on the outcomes for healthcare professionals who are assisted by advanced computing algorithms. Key Features: - Covers emerging technologies in biomedical engineering and healthcare that assist physicians in diagnosis, treatment, and surgical planning in a multidisciplinary context - Provides examples of technical use cases for artificial intelligence, machine learning and deep learning in medicine, with examples of different algorithms - Introduces readers to the concept of telemedicine and electronic healthcare systems - Provides implementations of disease prediction models for different diseases including cardiovascular diseases, diabetes and Alzheimer's disease - Summarizes key information for learners - Includes references for advanced readers The book serves as an essential reference for academic readers, as well as computer science enthusiasts who want to familiarize themselves with the practical computing techniques in the field of biomedical engineering (with a focus on medical imaging) and medical informatics.

Approaches and Applications of Deep Learning in Virtual Medical Care

Zaman, Noor,Gaur, Loveleen,Humayun, Mamoona
Approaches and Applications of Deep Learning in Virtual Medical Care Book PDF

Author : Zaman, Noor,Gaur, Loveleen,Humayun, Mamoona
Publisher : IGI Global
Page : 293 pages
File Size : 48,9 Mb
Release : 2022-02-25
Category : Computers
ISBN : 9781799889304

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Approaches and Applications of Deep Learning in Virtual Medical Care by Zaman, Noor,Gaur, Loveleen,Humayun, Mamoona Pdf

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.