[PDF] Data Fusion Techniques And Applications For Smart Healthcare eBook

Author : Amit Kumar Singh
Publisher : Elsevier
Page : 444 pages
File Size : 17,29 MB
Release : 2024-03-29
Category : Computers
ISBN : 0443132348

GET BOOK

Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences. Healthcare experts can make auscultation reports in text format; electrocardiograms can be printed in time series format, x-rays saved as images; volume can be provided through angiography; temporal information by echocardiograms, and 4D information extracted through flow MRI. Another typical source of variability is the existence of data from different time points, such as pre and post treatment, for instance. These large and highly diverse amounts of information need to be organized and mined in an appropriate way so that meaningful information can be extracted. New multimodal data fusion techniques are able to combine salient information into one single source to ensure better diagnostic accuracy and assessment. Data Fusion Techniques and Applications for Smart Healthcare covers cutting-edge research from both academia and industry with a particular emphasis on recent advances in algorithms and applications that involve combining multiple sources of medical information. This book can be used as a reference for practicing engineers, scientists, and researchers. It will also be useful for graduate students and practitioners from government and industry as well as healthcare technology professionals working on state-of-the-art information fusion solutions for healthcare applications. Presents broad coverage of applied case studies using data fusion techniques to mine, organize, and interpret medical data Investigates how data fusion techniques offer a new solution for dealing with massive amounts of medical data coming from diverse sources and multiple formats Focuses on identifying challenges, solutions, and new directions that will be useful for graduate students, researchers, and practitioners from government, academia, industry, and healthcare

Author : Chinmay Chakraborty
Publisher : Springer Nature
Page : 398 pages
File Size : 22,8 MB
Release : 2021-09-01
Category : Technology & Engineering
ISBN : 3030666336

GET BOOK

This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.

Author : Karthick, G.S.
Publisher : IGI Global
Page : 549 pages
File Size : 18,15 MB
Release : 2023-08-01
Category : Medical
ISBN : 1668489147

GET BOOK

Blockchain and artificial intelligence (AI) techniques play a crucial role in dealing with large amounts of heterogeneous, multi-scale, and multi-modal data coming from the internet of things (IoT) infrastructures. Therefore, further discussion on how the fusion of blockchain, IoT, and AI allows the design of models, mathematical models, methodologies, algorithms, evaluation benchmarks, and tools to address challenging problems related to health informatics, healthcare, and wellbeing is required. Contemporary Applications of Data Fusion for Advanced Healthcare Informatics covers the integration of IoT and AI to tackle applications in smart healthcare and discusses the efficient means to collect, monitor, control, optimize, model, and predict healthcare data using blockchain, AI, and IoT. The book also considers the advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. Covering key topics such as disruptive technology, electronic health records, and medical data, this premier reference source is ideal for computer scientists, nurses, doctors, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Author : Soumya De
Publisher :
Page : 0 pages
File Size : 32,47 MB
Release : 2013
Category : Image processing
ISBN :

GET BOOK

"Data fusion is a technique for combining data obtained from multiple sources for an enhanced detection or decision. Fusion of data can be done at the raw-data level, feature level or decision level. Applications of data fusion include defense (such as battlefield surveillance and autonomous vehicle control), medical diagnosis and structural health monitoring. Techniques for data fusion have been drawn from areas such as statistics, image processing, pattern recognition and computational intelligence. This dissertation includes investigation and development of methods to perform data fusion for nondestructive evaluation (NDE) and medical imaging applications. The general framework for these applications includes region-of-interest (ROI) detection followed by feature extraction and classification of the detected ROI. Image processing methods such as edge detection and projection-based methods were used for ROI detection. The features extracted from the detected ROIs include texture, color, shape/geometry and profile-based correlation. Analysis and classification of the detected ROIs was performed using feature- and decision-level data fusion techniques such as fuzzy-logic, statistical methods and voting algorithms"--Abstract, leaf iv

Author : Chinmay Chakraborty
Publisher : Academic Press
Page : 299 pages
File Size : 11,85 MB
Release : 2022-09-27
Category : Technology & Engineering
ISBN : 0323919367

GET BOOK

Implementation of Smart Healthcare Systems using AI, IoT, and Blockchain provides imperative research on the development of data fusion and analytics for healthcare and their implementation into current issues in a real-time environment. While highlighting IoT, bio-inspired computing, big data, and evolutionary programming, the book explores various concepts and theories of data fusion, IoT, and Big Data Analytics. It also investigates the challenges and methodologies required to integrate data from multiple heterogeneous sources, analytical platforms in healthcare sectors. This book is unique in the way that it provides useful insights into the implementation of a smart and intelligent healthcare system in a post-Covid-19 world using enabling technologies like Artificial Intelligence, Internet of Things, and blockchain in providing transparent, faster, secure and privacy preserved healthcare ecosystem for the masses. Explains how IoT can be integrated into the healthcare ecosystem for better diagnostics, monitoring and treatment Includes AI for predictive and preventive healthcare Describes blockchain for managing healthcare data to provide transparency, security and distributed storage Offers effective remote diagnostics and telemedicine approaches Highlights the importance of gold standard medical datasets for improved modeling and analysis

Author : Suparna Biswas
Publisher : Springer Nature
Page : 394 pages
File Size : 38,41 MB
Release : 2022-07-18
Category : Computers
ISBN : 9811914087

GET BOOK

This book provides both the developers and the users with an awareness of the challenges and opportunities of advancements in healthcare paradigm with the application and availability of advanced hardware, software, tools, technique or algorithm development stemming the Internet of Things. The book helps readers to bridge the gap in their three understanding of three major domains and their interconnections: Hardware tested and software APP development for data collection, intelligent protocols for analysis and knowledge extraction. Medical expertise to interpret extracted knowledge towards disease prediction or diagnosis and support. Security experts to ensure data correctness for precise advice. The book provides state-of-the-art overviews by active researchers, technically elaborating healthcare architectures/frameworks, protocols, algorithms, methodologies followed by experimental results and evaluation. Future direction and scope will be precisely documented for interested readers.

Author : Satya Prakash Yadav
Publisher : Walter de Gruyter GmbH & Co KG
Page : 486 pages
File Size : 11,69 MB
Release : 2024-09-23
Category : Science
ISBN : 3111435997

GET BOOK

The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.

Author : Prasant Kumar Pattnaik
Publisher : Springer Nature
Page : 228 pages
File Size : 14,23 MB
Release : 2021-09-30
Category : Technology & Engineering
ISBN : 9811653046

GET BOOK

This edited book helps researchers and practitioners to understand e-health, m-healthcare architecture through IoT and the state of the art in IoT counter measures. This book provides a comprehensive discussion on a functional framework for IoT-based healthcare systems, intelligent medicine box, RFID technology, HMI, cognitive interpretation, BCI, remote health monitoring systems, wearable sensors, WBAN, healthcare analytics, machine learning (ML) techniques for IoT-enabled healthcare services, security and privacy issues in IoT-based healthcare monitoring systems. The book discusses integration of IoT with big data and cloud computing for solving several real-time problems by the use of smart healthcare applications. In these applications, the cloud computing provides a common workplace for IoT and big data, big data provides data analytics technology and IoT provides the source of data. It serves as a reference resource for researchers and practitioners in academia and industry.

Author : David Hall
Publisher : CRC Press
Page : 564 pages
File Size : 22,98 MB
Release : 2001-06-20
Category : Technology & Engineering
ISBN : 1420038540

GET BOOK

The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut

Author : Peng Guo
Publisher :
Page : 121 pages
File Size : 10,74 MB
Release : 2018
Category :
ISBN :

GET BOOK

"Data fusion can be used to combine multiple data sources or modalities to facilitate enhanced visualization, analysis, detection, estimation, or classification. Data fusion can be applied at the raw-data, feature-based, and decision-based levels. Data fusion applications of different sorts have been built up in areas such as statistics, computer vision and other machine learning aspects. It has been employed in a variety of realistic scenarios such as medical diagnosis, clinical decision support, and structural health monitoring. This dissertation includes investigation and development of methods to perform data fusion for cervical cancer intraepithelial neoplasia (CIN) and a clinical decision support system. The general framework for these applications includes image processing followed by feature development and classification of the detected region of interest (ROI). Image processing methods such as k-means clustering based on color information, dilation, erosion and centroid locating methods were used for ROI detection. The features extracted include texture, color, nuclei-based and triangle features. Analysis and classification was performed using feature- and decision-level data fusion techniques such as support vector machine, statistical methods such as logistic regression, linear discriminant analysis and voting algorithms"--Abstract, page iv.