Medical Device Data And Modeling For Clinical Decision Making

Download Medical Device Data And Modeling For Clinical Decision Making full books in PDF, epub, and Kindle. Read online Medical Device Data And Modeling For Clinical Decision Making ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Medical Device Data and Modeling for Clinical Decision Making

Author : John R. Zaleski
Publisher : Artech House
ISBN 13 : 1608070956
Total Pages : 357 pages
Book Rating : 4.6/5 (8 download)

DOWNLOAD NOW!

Book Synopsis Medical Device Data and Modeling for Clinical Decision Making by : John R. Zaleski

Download or read book Medical Device Data and Modeling for Clinical Decision Making written by John R. Zaleski and published by Artech House. This book was released on 2011 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge volume is the first book that provides you with practical guidance on the use of medical device data for bioinformatics modeling purposes. You learn how to develop original methods for communicating with medical devices within healthcare enterprises and assisting with bedside clinical decision making. The book guides in the implementation and use of clinical decision support methods within the context of electronic health records in the hospital environment.This highly valuable reference also teaches budding biomedical engineers and bioinformaticists the practical benefits of using medical device data. Supported with over 100 illustrations, this all-in-one resource discusses key concepts in detail and then presents clear implementation examples to give you a complete understanding of how to use this knowledge in the field.

Medical Device Data and Modeling for Clinical Decision Making

Author : John Zaleski
Publisher :
ISBN 13 : 9781523117383
Total Pages : 344 pages
Book Rating : 4.1/5 (173 download)

DOWNLOAD NOW!

Book Synopsis Medical Device Data and Modeling for Clinical Decision Making by : John Zaleski

Download or read book Medical Device Data and Modeling for Clinical Decision Making written by John Zaleski and published by . This book was released on 2011 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge volume is the first book that provides you with practical guidance on the use of medical device data for bioinformatics modeling purposes. You learn how to develop original methods for communicating with medical devices within healthcare enterprises and assisting with bedside clinical decision making. The book guides in the implementation and use of clinical decision support methods within the context of electronic health records in the hospital environment. This highly valuable reference also teaches budding biomedical engineers and bioinformaticists the practical benefits of using medical device data. Supported with over 100 illustrations, this all-in-one resource discusses key concepts in detail and then presents clear implementation examples to give you a complete understanding of how to use this knowledge in the field.

Fundamentals of Clinical Data Science

Author : Pieter Kubben
Publisher : Springer
ISBN 13 : 3319997130
Total Pages : 219 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Fundamentals of Clinical Data Science by : Pieter Kubben

Download or read book Fundamentals of Clinical Data Science written by Pieter Kubben and published by Springer. This book was released on 2018-12-21 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modern Methods of Clinical Investigation

Author : Institute of Medicine
Publisher : National Academies Press
ISBN 13 : 0309042860
Total Pages : 241 pages
Book Rating : 4.3/5 (9 download)

DOWNLOAD NOW!

Book Synopsis Modern Methods of Clinical Investigation by : Institute of Medicine

Download or read book Modern Methods of Clinical Investigation written by Institute of Medicine and published by National Academies Press. This book was released on 1990-02-01 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very rapid pace of advances in biomedical research promises us a wide range of new drugs, medical devices, and clinical procedures. The extent to which these discoveries will benefit the public, however, depends in large part on the methods we choose for developing and testing them. Modern Methods of Clinical Investigation focuses on strategies for clinical evaluation and their role in uncovering the actual benefits and risks of medical innovation. Essays explore differences in our current systems for evaluating drugs, medical devices, and clinical procedures; health insurance databases as a tool for assessing treatment outcomes; the role of the medical profession, the Food and Drug Administration, and industry in stimulating the use of evaluative methods; and more. This book will be of special interest to policymakers, regulators, executives in the medical industry, clinical researchers, and physicians.

Reinventing Clinical Decision Support

Author : Paul Cerrato
Publisher : Taylor & Francis
ISBN 13 : 1000055558
Total Pages : 164 pages
Book Rating : 4.0/5 ( download)

DOWNLOAD NOW!

Book Synopsis Reinventing Clinical Decision Support by : Paul Cerrato

Download or read book Reinventing Clinical Decision Support written by Paul Cerrato and published by Taylor & Francis. This book was released on 2020-01-06 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it’s forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

Connected Medical Devices

Author : John Zaleski
Publisher : CRC Press
ISBN 13 : 1498757448
Total Pages : 232 pages
Book Rating : 4.4/5 (987 download)

DOWNLOAD NOW!

Book Synopsis Connected Medical Devices by : John Zaleski

Download or read book Connected Medical Devices written by John Zaleski and published by CRC Press. This book was released on 2015-03-27 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores how medical device integration (MDI) supports quality patient care and better clinical outcomes by reducing clinical documentation transcription errors, improving data accuracy and density within clinical records and ensuring the complete capture of medical device information on patients. It begins with a comprehensive overview of the types of medical devices in use and the ways in which those devices interact, then examines factors such as interoperability standards, patient identification, clinical alerts and regulatory and security considerations.

Trends and Innovations in Information Systems and Technologies

Author : Álvaro Rocha
Publisher : Springer Nature
ISBN 13 : 3030456978
Total Pages : 619 pages
Book Rating : 4.0/5 (34 download)

DOWNLOAD NOW!

Book Synopsis Trends and Innovations in Information Systems and Technologies by : Álvaro Rocha

Download or read book Trends and Innovations in Information Systems and Technologies written by Álvaro Rocha and published by Springer Nature. This book was released on 2020-05-17 with total page 619 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at the 2020 World Conference on Information Systems and Technologies (WorldCIST’20), held in Budva, Montenegro, from April 7 to 10, 2020. WorldCIST provides a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences with and challenges regarding various aspects of modern information systems and technologies. The main topics covered are A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human–Computer Interaction; J) Ethics, Computers & Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications.

Registries for Evaluating Patient Outcomes

Author : Agency for Healthcare Research and Quality/AHRQ
Publisher : Government Printing Office
ISBN 13 : 1587634333
Total Pages : 396 pages
Book Rating : 4.5/5 (876 download)

DOWNLOAD NOW!

Book Synopsis Registries for Evaluating Patient Outcomes by : Agency for Healthcare Research and Quality/AHRQ

Download or read book Registries for Evaluating Patient Outcomes written by Agency for Healthcare Research and Quality/AHRQ and published by Government Printing Office. This book was released on 2014-04-01 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.

Sharing Clinical Trial Data

Author : Institute of Medicine
Publisher : National Academies Press
ISBN 13 : 0309316324
Total Pages : 304 pages
Book Rating : 4.3/5 (93 download)

DOWNLOAD NOW!

Book Synopsis Sharing Clinical Trial Data by : Institute of Medicine

Download or read book Sharing Clinical Trial Data written by Institute of Medicine and published by National Academies Press. This book was released on 2015-04-20 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research--from funders, to researchers, to journals, to physicians, and ultimately, to patients.

Technological Innovation

Author : Annetine C. Gelijns
Publisher : National Academies
ISBN 13 :
Total Pages : 78 pages
Book Rating : 4.1/5 (351 download)

DOWNLOAD NOW!

Book Synopsis Technological Innovation by : Annetine C. Gelijns

Download or read book Technological Innovation written by Annetine C. Gelijns and published by National Academies. This book was released on 1989 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning and AI for Healthcare

Author : Arjun Panesar
Publisher : Apress
ISBN 13 : 1484237994
Total Pages : 390 pages
Book Rating : 4.4/5 (842 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and AI for Healthcare by : Arjun Panesar

Download or read book Machine Learning and AI for Healthcare written by Arjun Panesar and published by Apress. This book was released on 2019-02-04 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

Clinical Surveillance

Author : John R. Zaleski
Publisher : CRC Press
ISBN 13 : 1000196119
Total Pages : 123 pages
Book Rating : 4.0/5 (1 download)

DOWNLOAD NOW!

Book Synopsis Clinical Surveillance by : John R. Zaleski

Download or read book Clinical Surveillance written by John R. Zaleski and published by CRC Press. This book was released on 2020-11-05 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: For more than a decade, the focus of information technology has been on capturing and sharing data from a patient within an all-encompassing record (a.k.a. the electronic health record, EHR), to promote improved longitudinal oversight in the care of the patient. There are both those who agree and those who disagree as to whether this goal has been met, but it is certainly evolving. A key element to improved patient care has been the automated capture of data from durable medical devices that are the source of (mostly) objective data, from imagery to time-series histories of vital signs and spot-assessments of patients. The capture and use of these data to support clinical workflows have been written about and thoroughly debated. Yet, the use of these data for clinical guidance has been the subject of various papers published in respected medical journals, but without a coherent focus on the general subject of the clinically actionable benefits of objective medical device data for clinical decision-making purposes. Hence, the uniqueness of this book is in providing a single point-of-capture for the targeted clinical benefits of medical device data--both electronic- health-record-based and real-time--for improved clinical decision-making at the point of care, and for the use of these data to address and assess specific types of clinical surveillance. Clinical Surveillance: The Actionable Benefits of Objective Medical Device Data for Crucial Decision-Making focuses on the use of objective, continuously collected medical device data for the purpose of identifying patient deterioration, with a primary focus on those data normally obtained from both the higher-acuity care settings in intensive care units and the lower-acuity settings of general care wards. It includes examples of conditions that demonstrate earlier signs of deterioration including systemic inflammatory response syndrome, opioid-induced respiratory depression, shock induced by systemic failure, and more. The book provides education on how to use these data, such as for clinical interventions, in order to identify examples of how to guide care using automated durable medical device data from higher- and lower-acuity care settings. The book also includes real-world examples of applications that are of high value to clinical end-users and health systems.

Clinical Prediction Models

Author : Ewout W. Steyerberg
Publisher : Springer
ISBN 13 : 3030163997
Total Pages : 558 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Clinical Prediction Models by : Ewout W. Steyerberg

Download or read book Clinical Prediction Models written by Ewout W. Steyerberg and published by Springer. This book was released on 2019-07-22 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies

Secondary Analysis of Electronic Health Records

Author : MIT Critical Data
Publisher : Springer
ISBN 13 : 3319437429
Total Pages : 427 pages
Book Rating : 4.3/5 (194 download)

DOWNLOAD NOW!

Book Synopsis Secondary Analysis of Electronic Health Records by : MIT Critical Data

Download or read book Secondary Analysis of Electronic Health Records written by MIT Critical Data and published by Springer. This book was released on 2016-09-09 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.

An Introduction to Deep Reinforcement Learning

Author : Vincent Francois-Lavet
Publisher : Foundations and Trends (R) in Machine Learning
ISBN 13 : 9781680835380
Total Pages : 156 pages
Book Rating : 4.8/5 (353 download)

DOWNLOAD NOW!

Book Synopsis An Introduction to Deep Reinforcement Learning by : Vincent Francois-Lavet

Download or read book An Introduction to Deep Reinforcement Learning written by Vincent Francois-Lavet and published by Foundations and Trends (R) in Machine Learning. This book was released on 2018-12-20 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. Deep RL opens up many new applications in domains such as healthcare, robotics, smart grids, finance, and many more. This book provides the reader with a starting point for understanding the topic. Although written at a research level it provides a comprehensive and accessible introduction to deep reinforcement learning models, algorithms and techniques. Particular focus is on the aspects related to generalization and how deep RL can be used for practical applications. Written by recognized experts, this book is an important introduction to Deep Reinforcement Learning for practitioners, researchers and students alike.

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

Author : Rani, Geeta
Publisher : IGI Global
ISBN 13 : 1799827437
Total Pages : 586 pages
Book Rating : 4.7/5 (998 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning by : Rani, Geeta

Download or read book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning written by Rani, Geeta and published by IGI Global. This book was released on 2020-10-16 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Public Health Effectiveness of the FDA 510(k) Clearance Process

Author : Institute of Medicine
Publisher : National Academies Press
ISBN 13 : 0309162904
Total Pages : 141 pages
Book Rating : 4.3/5 (91 download)

DOWNLOAD NOW!

Book Synopsis Public Health Effectiveness of the FDA 510(k) Clearance Process by : Institute of Medicine

Download or read book Public Health Effectiveness of the FDA 510(k) Clearance Process written by Institute of Medicine and published by National Academies Press. This book was released on 2010-10-04 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Food and Drug Administration (FDA) is responsible for assuring that medical devices are safe and effective before they go on the market. As part of its assessment of FDA's premarket clearance process for medical devices, the IOM held a workshop June 14-15 to discuss how to best balance patient safety and technological innovation. This document summarizes the workshop.