Fundamentals of Clinical Data Science PDF Download

Author: Pieter Kubben
Publisher: Springer
ISBN: 3319997130
Category : Medical
Languages : en
Pages : 219

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Book Description
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Author: Monique Frize
Publisher: Springer Nature
ISBN: 3031016580
Category : Technology & Engineering
Languages : en
Pages : 69

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Book Description
Part II of Health Care Engineering begins with statistics on the occurrence of medical errors and adverse events, and includes some technological solutions. A chapter on electronic medical records follows. The knowledge management process divided into four steps is described; this includes a discussion on data acquisition, storage, and retrieval. The next two chapters discuss the other three steps of the knowledge management process (knowledge discovery, knowledge translation, knowledge integration and sharing). The last chapter briefly discusses usability studies and clinical trials. This two-part book consolidates material that supports courses on technology development and management issues in health care institutions. It can be useful for anyone involved in design, development, or research, whether in industry, hospitals, or government.

Author: Ervin Sejdic
Publisher: CRC Press
ISBN: 149877346X
Category : Medical
Languages : en
Pages : 624

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Book Description
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.

Author: Chen, Wei
Publisher: IGI Global
ISBN: 1466609761
Category : Medical
Languages : en
Pages : 537

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Book Description
"This book presents a unique integration of knowledge from multidisciplinary fields of engineering, industrial design, and medical science for the healthcare of a specific user group"--Provided by publisher.

Author: Robert Hoyt
Publisher: Lulu.com
ISBN: 179476173X
Category : Science
Languages : en
Pages : 260

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Book Description
Overview of biomedical data science -- Spreadsheet tools and tips -- Biostatistics primer -- Data visualization -- Introduction to databases -- Big data -- Bioinformatics and precision medicine -- Programming languages for data analysis -- Machine learning -- Artificial intelligence -- Biomedical data science resources -- Appendix A: Glossary -- Appendix B: Using data.world -- Appendix C: Chapter exercises.

Author: Peter D. Le Roux
Publisher: Elsevier Health Sciences
ISBN: 1455727539
Category : Medical
Languages : en
Pages : 647

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Book Description
Ideal for neurosurgeons, neurologists, neuroanesthesiologists, and intensivists, Monitoring in Neurocritical Care helps you use the latest technology to more successfully detect deteriorations in neurological status in the ICU. This neurosurgery reference offers in-depth coverage of state-of-the-art management strategies and techniques so you can effectively monitor your patients and ensure the best outcomes. Understand the scientific basis and rationale of particular monitoring techniques and how they can be used to assess neuro-ICU patients. Make optimal use of the most advanced technology, including transcranial Doppler sonography, transcranial color-coded sonography, measurements of jugular venous oxygen saturation, near-infrared spectroscopy, brain electrical monitoring techniques, and intracerebral microdialysis and techniques based on imaging. Apply multimodal monitoring for a more accurate view of brain function, and utilize the latest computer systems to integrate data at the bedside. Access practical information on basic principles, such as quality assurance, ethics, and ICU design.

Author: Cynthia McKinney, MBA, FHIMSS, PMP
Publisher: HIMSS Books
ISBN:
Category :
Languages : en
Pages : 234

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Book Description
Implementing business intelligence is a strategic activity that channels the outcomes of performance throughout the healthcare organization and its stakeholders. Additionally, business intelligence provides a visual, high-level view of historical trends, current operations and predictive analysis. Through insightful chapters written by industry experts and numerous, real-world case studies, this book demonstrates myriad practical and proven steps to developing a business intelligence solution, including pre- and post-implementation issues. This book is packed with information that will help you and your organization raise awareness of hidden business intelligence, generate improved analytical data and spread the access to this new information across the continuum of care. 2012.

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: M.Michael Shabot
Publisher: Springer Science & Business Media
ISBN: 1461226988
Category : Medical
Languages : en
Pages : 430

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Book Description
Modern critical care is characterized by the collection of large volumes of data and the making of urgent patient care decisions. The two do not necessarily go together easily. For many years the hope has been that ICU data management systems could play a meaningful role in ICU decision support. These hopes now have a basis in fact, and this book details the history, methodology, current status, and future prospects for critical care decision support systems. By focusing on real and operational systems, the book demonstrates the importance of integrating data from diverse clinical data sources; the keys to implementing clinically usable systems; the pitfalls to avoid in implementation; and the development of effective evaluation methods.

Author: Sheryl Brahnam
Publisher: Springer
ISBN: 3642160956
Category : Technology & Engineering
Languages : en
Pages : 235

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Book Description
This book is a continuation of the previous volumes of our series on Advanced Computational Intelligence Paradigms in Healthcare. The recent advances in computational intelligence paradigms have highlighted the need of intelligent systems in healthcare. This volume provides the reader a glimpse of the current state of the art in intelligent support system design in the field of healthcare. The book reports a sample of recent advances in: • Clinical Decision Support Systems • Rehabilitation Decision Support Systems • Technology Acceptance in Medical Decision Support Systems The book is directed to the researchers, professors, practitioner and students interested to design and develop intelligent decision support systems.