Neural Networks In Healthcare
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Introduction To Deep Learning For Healthcare
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Author : Cao Xiao
language : en
Publisher: Springer Nature
Release Date : 2021-11-11
Introduction To Deep Learning For Healthcare written by Cao Xiao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-11 with Medical categories.
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.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
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
Artificial Intelligence Applications For Health Care
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Author : Mitul Kumar Ahirwal
language : en
Publisher: CRC Press
Release Date : 2022-04-19
Artificial Intelligence Applications For Health Care written by Mitul Kumar Ahirwal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-19 with Business & Economics categories.
This book takes an interdisciplinary approach by covering topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided in this book. Key Features Covers computational Intelligence techniques like artificial neural networks, deep neural networks, and optimization algorithms for Healthcare systems Provides easy understanding for concepts like signal and image filtering techniques Includes discussion over data preprocessing and classification problems Details studies with medical signal (ECG, EEG, EMG) and image (X-ray, FMRI, CT) datasets Describes evolution parameters such as accuracy, precision, and recall etc. This book is aimed at researchers and graduate students in medical signal and image processing, machine and deep learning, and healthcare technologies.
Lean Thinking For Healthcare
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Author : Nilmini Wickramasinghe
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-04
Lean Thinking For Healthcare written by Nilmini Wickramasinghe and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-04 with Medical categories.
A growing, aging population; the rise to epidemic proportions of various chronic diseases; competing, often overlapping medical technologies; and of course, skyrocketing costs compounded by waste and inefficiency - these are just a few of the multifarious challenges currently facing healthcare delivery. An unexpected source of solutions is being imported from the manufacturing sector: lean thinking. Lean Principles for Healthcare presents a conceptual framework, management principles, and practical tools for professionals tasked with designing and implementing modern, streamlined healthcare systems or overhauling faulty ones. Focusing on core components such as knowledge management, e-health, patient-centeredness, and collaborative care, chapters illustrate lean concepts in action across specialties (as diverse as nursing, urology, and emergency care) and around the globe. Extended case examples show health systems responding to consumer needs and provider realities with equal efficiency and effectiveness, and improved quality and patient outcomes. Further, contributors tackle the gamut of technological, medical, cultural, and business issues, among them: Initiatives of service-oriented architecture towards performance improvement Adapted lean thinking for emergency departments Lean thinking in dementia care through smart assistive technology Supporting preventive healthcare with persuasive services Value stream mapping for lean healthcare A technology mediated solution to reduce healthcare disparities Geared toward both how lean ideas can be carried out and how they are being used successfully in the real world, Lean Principles for Healthcare not only brings expert knowledge to healthcare managers and health services researchers but to all who have an interest in superior healthcare delivery.
Design And Implementation Of Healthcare Biometric Systems
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Author : Kisku, Dakshina Ranjan
language : en
Publisher: IGI Global
Release Date : 2019-01-11
Design And Implementation Of Healthcare Biometric Systems written by Kisku, Dakshina Ranjan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-11 with Medical categories.
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.
Data Analytics In Bioinformatics
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Author : Rabinarayan Satpathy
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-20
Data Analytics In Bioinformatics written by Rabinarayan Satpathy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-20 with Computers categories.
Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.
Deep Learning For Medical Image Analysis
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2017-01-18
Deep Learning For Medical Image Analysis written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Computers categories.
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
Neural Networks In Healthcare Potential And Challenges
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Author : Begg, Rezaul
language : en
Publisher: IGI Global
Release Date : 2006-01-31
Neural Networks In Healthcare Potential And Challenges written by Begg, Rezaul and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-31 with Medical categories.
"This book covers state-of-the-art applications in many areas of medicine and healthcare"--Provided by publisher.
Machine Learning And Deep Learning Techniques For Medical Science
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Author : K. Gayathri Devi
language : en
Publisher: CRC Press
Release Date : 2022-05-11
Machine Learning And Deep Learning Techniques For Medical Science written by K. Gayathri Devi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-11 with Technology & Engineering categories.
The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).
World Congress Of Medical Physics And Biomedical Engineering 2006
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Author : Sun I. Kim
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-05
World Congress Of Medical Physics And Biomedical Engineering 2006 written by Sun I. Kim and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-05 with Technology & Engineering categories.
These proceedings of the World Congress 2006, the fourteenth conference in this series, offer a strong scientific program covering a wide range of issues and challenges which are currently present in Medical physics and Biomedical Engineering. About 2,500 peer reviewed contributions are presented in a six volume book, comprising 25 tracks, joint conferences and symposia, and including invited contributions from well known researchers in this field.