Deep Learning In Healthcare

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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 : 41,5 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.

Introduction to Deep Learning for Healthcare

Cao Xiao,Jimeng Sun
Introduction to Deep Learning for Healthcare Book PDF

Author : Cao Xiao,Jimeng Sun
Publisher : Springer Nature
Page : 236 pages
File Size : 54,7 Mb
Release : 2021-11-11
Category : Medical
ISBN : 9783030821845

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Introduction to Deep Learning for Healthcare by Cao Xiao,Jimeng Sun Pdf

This textbook presents deep learning models and their healthcare applications. It focuses on rich health data and deep learning models that can effectively model health data. Healthcare data: Among all healthcare technologies, electronic health records (EHRs) had vast adoption and a significant impact on healthcare delivery in recent years. One crucial benefit of EHRs is to capture all the patient encounters with rich multi-modality data. Healthcare data include both structured and unstructured information. Structured data include various medical codes for diagnoses and procedures, lab results, and medication information. Unstructured data contain 1) clinical notes as text, 2) medical imaging data such as X-rays, echocardiogram, and magnetic resonance imaging (MRI), and 3) time-series data such as the electrocardiogram (ECG) and electroencephalogram (EEG). Beyond the data collected during clinical visits, patient self-generated/reported data start to grow thanks to wearable sensors’ increasing use. The authors present deep learning case studies on all data described. Deep learning models: Neural network models are a class of machine learning methods with a long history. Deep learning models are neural networks of many layers, which can extract multiple levels of features from raw data. Deep learning applied to healthcare is a natural and promising direction with many initial successes. The authors cover deep neural networks, convolutional neural networks, recurrent neural networks, embedding methods, autoencoders, attention models, graph neural networks, memory networks, and generative models. It’s presented with concrete healthcare case studies such as clinical predictive modeling, readmission prediction, phenotyping, x-ray classification, ECG diagnosis, sleep monitoring, automatic diagnosis coding from clinical notes, automatic deidentification, medication recommendation, drug discovery (drug property prediction and molecule generation), and clinical trial matching. This textbook targets graduate-level students focused on deep learning methods and their healthcare applications. It can be used for the concepts of deep learning and its applications as well. Researchers working in this field will also find this book to be extremely useful and valuable for their research.

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 : 41,8 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.

Machine Learning with Health Care Perspective

Vishal Jain,Jyotir Moy Chatterjee
Machine Learning with Health Care Perspective Book PDF

Author : Vishal Jain,Jyotir Moy Chatterjee
Publisher : Springer Nature
Page : 418 pages
File Size : 51,7 Mb
Release : 2020-03-09
Category : Technology & Engineering
ISBN : 9783030408503

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Machine Learning with Health Care Perspective by Vishal Jain,Jyotir Moy Chatterjee Pdf

This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.

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 : 52,6 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.

Machine Learning and AI for Healthcare

Arjun Panesar
Machine Learning and AI for Healthcare Book PDF

Author : Arjun Panesar
Publisher : Apress
Page : 390 pages
File Size : 50,5 Mb
Release : 2019-02-04
Category : Computers
ISBN : 9781484237991

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Machine Learning and AI for Healthcare by Arjun Panesar Pdf

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

Deep Medicine

Eric Topol
Deep Medicine Book PDF

Author : Eric Topol
Publisher : Basic Books
Page : 373 pages
File Size : 51,9 Mb
Release : 2019-03-12
Category : Health & Fitness
ISBN : 9781541644649

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Deep Medicine by Eric Topol Pdf

A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Design and Implementation of Healthcare Biometric Systems

Kisku, Dakshina Ranjan,Gupta, Phalguni,Sing, Jamuna Kanta
Design and Implementation of Healthcare Biometric Systems Book PDF

Author : Kisku, Dakshina Ranjan,Gupta, Phalguni,Sing, Jamuna Kanta
Publisher : IGI Global
Page : 300 pages
File Size : 50,6 Mb
Release : 2019-01-11
Category : Medical
ISBN : 9781522575269

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Design and Implementation of Healthcare Biometric Systems by Kisku, Dakshina Ranjan,Gupta, Phalguni,Sing, Jamuna Kanta Pdf

Healthcare sectors often deal with a large amount of data related to patients’ care and hospital workforce management. Mistakes occur, and the impending results are disastrous for individuals’ personal identity information. However, an innovative and reliable way to safeguard the identity of individuals and provide protection of medical records from criminals is already in effect. Design and Implementation of Healthcare Biometric Systems provides innovative insights into medical identity theft and the benefits behind biometrics technologies that could be offered to protect medical records from hackers and malicious users. The content within this publication represents the work of ASD screening systems, healthcare management, and patient rehabilitation. It is designed for educators, researchers, faculty members, industry practitioners, graduate students, and professionals working with healthcare services and covers topics centered on understanding the practical essence of next-generation healthcare biometrics systems and future research directions.

Demystifying Big Data and Machine Learning for Healthcare

Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
Demystifying Big Data and Machine Learning for Healthcare Book PDF

Author : Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
Publisher : CRC Press
Page : 233 pages
File Size : 51,6 Mb
Release : 2017-02-15
Category : Medical
ISBN : 9781315389301

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Demystifying Big Data and Machine Learning for Healthcare by Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz Pdf

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Deep Learning Applications in Medical Imaging

Saxena, Sanjay,Paul, Sudip
Deep Learning Applications in Medical Imaging Book PDF

Author : Saxena, Sanjay,Paul, Sudip
Publisher : IGI Global
Page : 274 pages
File Size : 43,9 Mb
Release : 2020-10-16
Category : Medical
ISBN : 9781799850724

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Deep Learning Applications in Medical Imaging by Saxena, Sanjay,Paul, Sudip Pdf

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.

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 : 49,9 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 : 43,7 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

Artificial Intelligence in Healthcare

Adam Bohr,Kaveh Memarzadeh
Artificial Intelligence in Healthcare Book PDF

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

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

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 : 544 pages
File Size : 44,9 Mb
Release : 2023-12-01
Category : Computers
ISBN : 9780323858885

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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. · 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

Applications of Deep Learning and Big IoT on Personalized Healthcare Services

Wason, Ritika,Goyal, Dinesh,Jain, Vishal,Balamurugan, S.,Baliyan, Anupam
Applications of Deep Learning and Big IoT on Personalized Healthcare Services Book PDF

Author : Wason, Ritika,Goyal, Dinesh,Jain, Vishal,Balamurugan, S.,Baliyan, Anupam
Publisher : IGI Global
Page : 248 pages
File Size : 51,9 Mb
Release : 2020-02-07
Category : Medical
ISBN : 9781799821021

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Applications of Deep Learning and Big IoT on Personalized Healthcare Services by Wason, Ritika,Goyal, Dinesh,Jain, Vishal,Balamurugan, S.,Baliyan, Anupam Pdf

Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes. Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.