Ontology-Based Information Retrieval for Healthcare Systems
Ontology-Based Information Retrieval for Healthcare Systems

Author: Vishal Jain

Publisher: John Wiley & Sons

Published: 2020-07-29

Total Pages: 384

ISBN-13: 1119641381

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With the advancements of semantic web, ontology has become the crucial mechanism for representing concepts in various domains. For research and dispersal of customized healthcare services, a major challenge is to efficiently retrieve and analyze individual patient data from a large volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for clinical information systems so that the pertinent information can be mined from large amount of distributed data. This unique and groundbreaking book highlights the key advances in ontology-based information retrieval techniques being applied in the healthcare domain and covers the following areas: Semantic data integration in e-health care systems Keyword-based medical information retrieval Ontology-based query retrieval support for e-health implementation Ontologies as a database management system technology for medical information retrieval Information integration using contextual knowledge and ontology merging Collaborative ontology-based information indexing and retrieval in health informatics An ontology-based text mining framework for vulnerability assessment in health and social care An ontology-based multi-agent system for matchmaking patient healthcare monitoring A multi-agent system for querying heterogeneous data sources with ontologies for reducing cost of customized healthcare systems A methodology for ontology based multi agent systems development Ontology based systems for clinical systems: validity, ethics and regulation

Intelligent Information Retrieval for Healthcare Systems
Intelligent Information Retrieval for Healthcare Systems

Author: Parma Nand Astya

Publisher: Nova Science Publishers

Published: 2021-12-02

Total Pages: 265

ISBN-13: 9781685073657

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"Ontology-based information extraction is considered as an effective method to improve the performance of information extraction (IE) systems. For research and disbursal of customized healthcare services, a major challenge is to efficiently retrieve and analyze the individual patient data from a large volume of heterogeneous data over a long span of time. This requires effective ontology-based information retrieval approaches for clinical information systems. This book is an attempt to highlight the key advances in ontology-based information retrieval techniques especially in the healthcare domain. The varied chapters attempt to uncover the current challenges in the application of ontology-based information retrieval techniques to the healthcare systems. This book is the first of its kind that highlights the ontology-driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems. It can serve as a textbook for courses in healthcare systems. It can also serve as a reference book to medical practitioners and researchers involved in implementing as well as providing customized health care solutions to patients"--

Ontology-Based Information Retrieval for Healthcare Systems
Ontology-Based Information Retrieval for Healthcare Systems

Author: Vishal Jain

Publisher: John Wiley & Sons

Published: 2020-07-28

Total Pages: 384

ISBN-13: 1119640482

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With the advancements of semantic web, ontology has become the crucial mechanism for representing concepts in various domains. For research and dispersal of customized healthcare services, a major challenge is to efficiently retrieve and analyze individual patient data from a large volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for clinical information systems so that the pertinent information can be mined from large amount of distributed data. This unique and groundbreaking book highlights the key advances in ontology-based information retrieval techniques being applied in the healthcare domain and covers the following areas: Semantic data integration in e-health care systems Keyword-based medical information retrieval Ontology-based query retrieval support for e-health implementation Ontologies as a database management system technology for medical information retrieval Information integration using contextual knowledge and ontology merging Collaborative ontology-based information indexing and retrieval in health informatics An ontology-based text mining framework for vulnerability assessment in health and social care An ontology-based multi-agent system for matchmaking patient healthcare monitoring A multi-agent system for querying heterogeneous data sources with ontologies for reducing cost of customized healthcare systems A methodology for ontology based multi agent systems development Ontology based systems for clinical systems: validity, ethics and regulation

Intelligent Information Retrieval for Healthcare Systems
Intelligent Information Retrieval for Healthcare Systems

Author: Parma Nand

Publisher: Nova Science Publishers

Published: 2021

Total Pages: 0

ISBN-13: 9781685073015

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Ontology-based information extraction is considered as an effective method to improve the performance of information extraction (IE) systems. For research and disbursal of customized healthcare services, a major challenge is to efficiently retrieve and analyse the individual patient data from a large volume of heterogeneous data over a long span of time. This requires effective ontology-based information retrieval approaches for clinical information systems. This book is an attempt to highlight the key advances in ontology-based information retrieval techniques especially in the healthcare domain. The varied chapters attempt to uncover the current challenges in the application of ontology-based information retrieval techniques to the healthcare systems. This book is the first of its kind that highlights the ontology-driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems. It can serve as a textbook for courses in healthcare systems. It can also serve as a reference book to medical practitioners and researchers involved in implementing as well as providing customised health care solutions to patients.

Artificial Intelligence in Healthcare
Artificial Intelligence in Healthcare

Author: Adam Bohr

Publisher: Academic Press

Published: 2020-06-21

Total Pages: 385

ISBN-13: 0128184396

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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

Semantic Web for Effective Healthcare Systems
Semantic Web for Effective Healthcare Systems

Author: Vishal Jain

Publisher: John Wiley & Sons

Published: 2021-11-12

Total Pages: 352

ISBN-13: 1119764157

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SEMANTIC WEB FOR EFFECTIVE HEALTHCARE SYSTEMS The book summarizes the trends and current research advances in web semantics, delineating the existing tools, techniques, methodologies, and research solutions Semantic Web technologies have the opportunity to transform the way healthcare providers utilize technology to gain insights and knowledge from their data and make treatment decisions. Both Big Data and Semantic Web technologies can complement each other to address the challenges and add intelligence to healthcare management systems. The aim of this book is to analyze the current status on how the semantic web is used to solve health data integration and interoperability problems, and how it provides advanced data linking capabilities that can improve search and retrieval of medical data. Chapters analyze the tools and approaches to semantic health data analysis and knowledge discovery. The book discusses the role of semantic technologies in extracting and transforming healthcare data before storing it in repositories. It also discusses different approaches for integrating heterogeneous healthcare data. This innovative book offers: The first of its kind and highlights only the ontology driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems; Presents a comprehensive examination of the emerging research in areas of the semantic web; Discusses studies on new research areas including ontological engineering, semantic annotation and semantic sentiment analysis; Helps readers understand key concepts in semantic web applications for the biomedical engineering and healthcare fields; Includes coverage of key application areas of the semantic web. Audience: Researchers and graduate students in computer science, biomedical engineering, electronic and software engineering, as well as industry scientific researchers, clinicians, and systems managers in biomedical fields.

Diagnostic Applications of Health Intelligence and Surveillance Systems
Diagnostic Applications of Health Intelligence and Surveillance Systems

Author: Yadav, Divakar

Publisher: IGI Global

Published: 2021-01-15

Total Pages: 332

ISBN-13: 1799865282

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Health surveillance and intelligence play an important role in modern health systems as more data must be collected and analyzed. It is crucial that this data is interpreted and analyzed effectively and efficiently in order to assist with diagnoses and predictions. Diagnostic Applications of Health Intelligence and Surveillance Systems is an essential reference book that examines recent studies that are driving artificial intelligence in the health sector and helping practitioners to predict and diagnose diseases. Chapters within the book focus on health intelligence and how health surveillance data can be made useful and meaningful. Covering topics that include computational intelligence, data analytics, mobile health, and neural networks, this book is crucial for healthcare practitioners, IT specialists, academicians, researchers, and students.

Innovative Systems for Intelligent Health Informatics
Innovative Systems for Intelligent Health Informatics

Author: Faisal Saeed

Publisher: Springer Nature

Published: 2021-05-05

Total Pages: 1262

ISBN-13: 303070713X

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This book presents the papers included in the proceedings of the 5th International Conference of Reliable Information and Communication Technology 2020 (IRICT 2020) that was held virtually on December 21–22, 2020. The main theme of the book is “Innovative Systems for Intelligent Health Informatics”. A total of 140 papers were submitted to the conference, but only 111 papers were published in this book. The book presents several hot research topics which include health informatics, bioinformatics, information retrieval, artificial intelligence, soft computing, data science, big data analytics, Internet of things (IoT), intelligent communication systems, information security, information systems, and software engineering.

Intelligent Healthcare Systems
Intelligent Healthcare Systems

Author: Vania V. Estrela

Publisher: CRC Press

Published: 2023-08-04

Total Pages: 399

ISBN-13: 1000954323

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The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems’ design practices and computational intelligence tactics for medical usage. The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.

Biomedical Data Mining for Information Retrieval
Biomedical Data Mining for Information Retrieval

Author: Sujata Dash

Publisher: John Wiley & Sons

Published: 2021-08-24

Total Pages: 450

ISBN-13: 111971124X

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BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.