Advances in Healthcare Informatics and Analytics PDF Download

Author: Ashish Gupta
Publisher: Springer
ISBN: 3319232940
Category : Medical
Languages : en
Pages : 267

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Book Description
This important new volume presents recent research in healthcare information technology and analytics. Individual chapters look at such issues as the impact of technology failure on electronic prescribing behavior in primary care; attitudes toward electronic health records; a latent growth modeling approach to understanding lifestyle decisions based on patient historical data; designing an integrated surgical care delivery system using axiomatic design and petri net modeling; and failure in a dynamic decision environment, particularly in treating patients with a chronic disease. Other chapters look at such topics as the impact of information technology integration in integrated delivery systems; operations and supply chain control for inventory management in a health system pharmacy; decision-theoretic assistants based on contextual gesture recognition; evaluating emergency response medical information systems; clinical decision support in critical care; virtual worlds in healthcare; and natural language processing for understanding contraceptive use at the VA.

Author: Aziz Sheikh
Publisher: Academic Press
ISBN: 0128095253
Category : Medical
Languages : en
Pages : 335

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Book Description
Key Advances in Clinical Informatics: Transforming Health Care through Health Information Technology provides a state-of-the-art overview of the most current subjects in clinical informatics. Leading international authorities write short, accessible, well-referenced chapters which bring readers up-to-date with key developments and likely future advances in the relevant subject areas. This book encompasses topics such as inpatient and outpatient clinical information systems, clinical decision support systems, health information technology, genomics, mobile health, telehealth and cloud-based computing. Additionally, it discusses privacy, confidentiality and security required for health data. Edited by internationally recognized authorities in the field of clinical informatics, the book is a valuable resource for medical/nursing students, clinical informaticists, clinicians in training, practicing clinicians and allied health professionals with an interest in health informatics. - Presents a state-of-the-art overview of the most current subjects in clinical informatics. - Provides summary boxes of key points at the beginning of each chapter to impart relevant messages in an easily digestible fashion - Includes internationally acclaimed experts contributing to chapters in one accessible text - Explains and illustrates through international case studies to show how the evidence presented is applied in a real world setting

Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 0128156368
Category : Science
Languages : en
Pages : 342

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Book Description
Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. - Covers data analysis, management and security concepts and tools in the healthcare domain - Highlights electronic medical health records and patient information records - Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining - Includes multidisciplinary contributions in relation to healthcare applications and challenges

Author: Mayuri Mehta
Publisher: CRC Press
ISBN: 1000477762
Category : Computers
Languages : en
Pages : 363

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Book Description
Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications focuses on automated analytical techniques for healthcare applications used to extract knowledge from a vast amount of data. It brings together a variety of different aspects of the healthcare system and aids in the decision-making processes for healthcare professionals. The editors connect four contemporary areas of research rarely brought together in one book: artificial intelligence, big data analytics, knowledge modelling, and healthcare. They present state-of-the-art research from the healthcare sector, including research on medical imaging, healthcare analysis, and the applications of artificial intelligence in drug discovery. This book is intended for data scientists, academicians, and industry professionals in the healthcare sector.

Author: Chandan K. Reddy
Publisher: CRC Press
ISBN: 148223212X
Category : Business & Economics
Languages : en
Pages : 756

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Book Description
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available

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.

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: David Riaño
Publisher: Springer
ISBN: 303021642X
Category : Computers
Languages : en
Pages : 431

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Book Description
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

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: Qiang Yang
Publisher: Springer Nature
ISBN: 3030630765
Category : Computers
Languages : en
Pages : 291

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Book Description
This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”