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Author: Nguyen Thi Dieu Linh
Publisher: Springer Nature
ISBN: 9811630291
Category : Technology & Engineering
Languages : en
Pages : 91
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Book Description
This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.
Author: Nguyen Thi Dieu Linh
Publisher: Springer Nature
ISBN: 9811630291
Category : Technology & Engineering
Languages : en
Pages : 91
Get Book Here
Book Description
This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.
Author: J. Mantas
Publisher: IOS Press
ISBN: 1614999872
Category : Medical
Languages : en
Pages : 422
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Book Description
The latest developments in data, informatics and technology continue to enable health professionals and informaticians to improve healthcare for the benefit of patients everywhere. This book presents full papers from ICIMTH 2019, the 17th International Conference on Informatics, Management and Technology in Healthcare, held in Athens, Greece from 5 to 7 July 2019. Of the 150 submissions received, 95 were selected for presentation at the conference following review and are included here. The conference focused on increasing and improving knowledge of healthcare applications spanning the entire spectrum from clinical and health informatics to public health informatics as applied in the healthcare domain. The field of biomedical and health informatics is examined in a very broad framework, presenting the research and application outcomes of informatics from cell to population and exploring a number of technologies such as imaging, sensors, and biomedical equipment, together with management and organizational aspects including legal and social issues. Setting research priorities in health informatics is also addressed. Providing an overview of the latest developments in health informatics, the book will be of interest to all those working in the field.
Author: Leo Anthony Celi
Publisher: Springer Nature
ISBN: 3030479943
Category : Medical
Languages : en
Pages : 471
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Book Description
This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Author: Andreas Holzinger
Publisher: Springer
ISBN: 3319504789
Category : Computers
Languages : en
Pages : 503
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Book Description
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
Author: A.V. Gundlapalli
Publisher: IOS Press
ISBN: 1614998302
Category : Medical
Languages : en
Pages : 1440
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Book Description
Medical informatics is a field which continues to evolve with developments and improvements in foundational methods, applications, and technology, constantly offering opportunities for supporting the customization of healthcare to individual patients. This book presents the proceedings of the 16th World Congress of Medical and Health Informatics (MedInfo2017), held in Hangzhou, China, in August 2017, which also marked the 50th anniversary of the International Medical Informatics Association (IMIA). The central theme of MedInfo2017 was "Precision Healthcare through Informatics", and the scientific program was divided into five tracks: connected and digital health; human data science; human, organizational, and social aspects; knowledge management and quality; and safety and patient outcomes. The 249 accepted papers and 168 posters included here span the breadth and depth of sub-disciplines in biomedical and health informatics, such as clinical informatics; nursing informatics; consumer health informatics; public health informatics; human factors in healthcare; bioinformatics; translational informatics; quality and safety; research at the intersection of biomedical and health informatics; and precision medicine. The book will be of interest to all those who wish to keep pace with advances in the science, education, and practice of biomedical and health informatics worldwide.
Author: Sergio Consoli
Publisher: Springer
ISBN: 3030052494
Category : Computers
Languages : en
Pages : 367
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Book Description
This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.
Author: Miltiadis Lytras
Publisher: Academic Press
ISBN: 0128190442
Category : Medical
Languages : en
Pages : 441
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Book Description
Innovation in Health Informatics: A Smart Healthcare Primer explains how the most recent advances in information and communication technologies have paved the way for new breakthroughs in healthcare. The book showcases current and prospective applications in a context defined by an imperative to deliver efficient, patient-centered and sustainable healthcare systems. Topics discussed include big data, medical data analytics, artificial intelligence, machine learning, virtual and augmented reality, 5g and sensors, Internet of Things, nanotechnologies and biotechnologies. Additionally, there is a discussion on social issues and policy- making for the implementation of smart healthcare. This book is a valuable resource for undergraduate and graduate students, practitioners, researchers, clinicians and data scientists who are interested in how to explore the intersections between bioinformatics and health informatics. - Provides a holistic discussion on the new landscape of medical technologies, including big data, analytics, artificial intelligence, machine learning, virtual and augmented reality, 5g and sensors, Internet of Things, nanotechnologies and biotechnologies - Presents a case study driven approach, with references to real-world applications and systems - Discusses topics with a research-oriented approach that aims to promote research skills and competencies of readers
Author: Peter Mccaffrey
Publisher: Academic Press
ISBN: 0128149167
Category : Medical
Languages : en
Pages : 342
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Book Description
An Introduction to Healthcare Informatics: Building Data-Driven Tools bridges the gap between the current healthcare IT landscape and cutting edge technologies in data science, cloud infrastructure, application development and even artificial intelligence. Information technology encompasses several rapidly evolving areas, however healthcare as a field suffers from a relatively archaic technology landscape and a lack of curriculum to effectively train its millions of practitioners in the skills they need to utilize data and related tools. The book discusses topics such as data access, data analysis, big data current landscape and application architecture. Additionally, it encompasses a discussion on the future developments in the field. This book provides physicians, nurses and health scientists with the concepts and skills necessary to work with analysts and IT professionals and even perform analysis and application architecture themselves. - Presents case-based learning relevant to healthcare, bringing each concept accompanied by an example which becomes critical when explaining the function of SQL, databases, basic models etc. - Provides a roadmap for implementing modern technologies and design patters in a healthcare setting, helping the reader to understand both the archaic enterprise systems that often exist in hospitals as well as emerging tools and how they can be used together - Explains healthcare-specific stakeholders and the management of analytical projects within healthcare, allowing healthcare practitioners to successfully navigate the political and bureaucratic challenges to implementation - Brings diagrams for each example and technology describing how they operate individually as well as how they fit into a larger reference architecture built upon throughout the book
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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Book Description
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
Author: Dong Xu
Publisher: Springer
ISBN: 3319449818
Category : Medical
Languages : en
Pages : 214
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Book Description
This book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis techniques. Each chapter offers a summary of the field and a sample analysis. Also covered are telehealth infrastructure, healthcare information association rules, methods for mass spectrometry imaging, environmental biodiversity, and the global nonlinear fitness function for protein structures. Diseases are addressed in chapters on functional annotation of lncRNAs in human disease, metabolomics characterization of human diseases, disease risk factors using SNP data and Bayesian methods, and imaging informatics for diagnostic imaging marker selection. With the exploding accumulation of Electronic Health Records (EHRs), there is an urgent need for computer-aided analysis of heterogeneous biomedical datasets. Biomedical data is notorious for its diversified scales, dimensions, and volumes, and requires interdisciplinary technologies for visual illustration and digital characterization. Various computer programs and servers have been developed for these purposes by both theoreticians and engineers. This book is an essential reference for investigating the tools available for analyzing heterogeneous biomedical data. It is designed for professionals, researchers, and practitioners in biomedical engineering, diagnostics, medical electronics, and related industries.
