Medical Data Sharing Harmonization and Analytics

Medical Data Sharing  Harmonization and Analytics
Author: Vasileios Pezoulas,Themis Exarchos,Dimitrios I Fotiadis
Publsiher: Academic Press
Total Pages: 382
Release: 2020-01-05
ISBN 10: 0128165596
ISBN 13: 9780128165591
Language: EN, FR, DE, ES & NL

Medical Data Sharing Harmonization and Analytics Book Review:

Medical Data Sharing, Harmonization and Analytics serves as the basis for understanding the rapidly evolving field of medical data harmonization combined with the latest cloud infrastructures for storing the harmonized (shared) data. Chapters cover the latest research and applications on data sharing and protection in the medical domain, cohort integration through the recent advancements in data harmonization, cloud computing for storing and securing the patient data, and data analytics for effectively processing the harmonized data. Examines the unmet needs in chronic diseases as a part of medical data sharing Discusses ethical, legal and privacy issues as part of data protection Combines data harmonization and big data analytics strategies in shared medical data, along with relevant case studies in chronic diseases

8th European Medical and Biological Engineering Conference

8th European Medical and Biological Engineering Conference
Author: Tomaz Jarm,Aleksandra Cvetkoska,Samo Mahnič-Kalamiza,Damijan Miklavcic
Publsiher: Springer Nature
Total Pages: 1172
Release: 2020-11-29
ISBN 10: 3030646106
ISBN 13: 9783030646103
Language: EN, FR, DE, ES & NL

8th European Medical and Biological Engineering Conference Book Review:

This book aims at informing on new trends, challenges and solutions, in the multidisciplinary field of biomedical engineering. It covers traditional biomedical engineering topics, as well as innovative applications such as artificial intelligence in health care, tissue engineering , neurotechnology and wearable devices. Further topics include mobile health and electroporation-based technologies, as well as new treatments in medicine. Gathering the proceedings of the 8th European Medical and Biological Engineering Conference (EMBEC 2020), held on November 29 - December 3, 2020, in Portorož, Slovenia, this book bridges fundamental and clinically-oriented research, emphasizing the role of education, translational research and commercialization of new ideas in biomedical engineering. It aims at inspiring and fostering communication and collaboration between engineers, physicists, biologists, physicians and other professionals dealing with cutting-edge themes in and advanced technologies serving the broad field of biomedical engineering.

Sharing Clinical Research Data

Sharing Clinical Research Data
Author: Institute of Medicine,Board on Health Care Services,Board on Health Sciences Policy,Roundtable on Translating Genomic-Based Research for Health,National Cancer Policy Forum,Forum on Neuroscience and Nervous System Disorders,Forum on Drug Discovery, Development, and Translation
Publsiher: National Academies Press
Total Pages: 156
Release: 2013-06-07
ISBN 10: 0309268745
ISBN 13: 9780309268745
Language: EN, FR, DE, ES & NL

Sharing Clinical Research Data Book Review:

Pharmaceutical companies, academic researchers, and government agencies such as the Food and Drug Administration and the National Institutes of Health all possess large quantities of clinical research data. If these data were shared more widely within and across sectors, the resulting research advances derived from data pooling and analysis could improve public health, enhance patient safety, and spur drug development. Data sharing can also increase public trust in clinical trials and conclusions derived from them by lending transparency to the clinical research process. Much of this information, however, is never shared. Retention of clinical research data by investigators and within organizations may represent lost opportunities in biomedical research. Despite the potential benefits that could be accrued from pooling and analysis of shared data, barriers to data sharing faced by researchers in industry include concerns about data mining, erroneous secondary analyses of data, and unwarranted litigation, as well as a desire to protect confidential commercial information. Academic partners face significant cultural barriers to sharing data and participating in longer term collaborative efforts that stem from a desire to protect intellectual autonomy and a career advancement system built on priority of publication and citation requirements. Some barriers, like the need to protect patient privacy, pre- sent challenges for both sectors. Looking ahead, there are also a number of technical challenges to be faced in analyzing potentially large and heterogeneous datasets. This public workshop focused on strategies to facilitate sharing of clinical research data in order to advance scientific knowledge and public health. While the workshop focused on sharing of data from preplanned interventional studies of human subjects, models and projects involving sharing of other clinical data types were considered to the extent that they provided lessons learned and best practices. The workshop objectives were to examine the benefits of sharing of clinical research data from all sectors and among these sectors, including, for example: benefits to the research and development enterprise and benefits to the analysis of safety and efficacy. Sharing Clinical Research Data: Workshop Summary identifies barriers and challenges to sharing clinical research data, explores strategies to address these barriers and challenges, including identifying priority actions and "low-hanging fruit" opportunities, and discusses strategies for using these potentially large datasets to facilitate scientific and public health advances.

Registries for Evaluating Patient Outcomes

Registries for Evaluating Patient Outcomes
Author: Agency for Healthcare Research and Quality/AHRQ
Publsiher: Government Printing Office
Total Pages: 356
Release: 2014-04-01
ISBN 10: 1587634333
ISBN 13: 9781587634338
Language: EN, FR, DE, ES & NL

Registries for Evaluating Patient Outcomes Book Review:

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.

Patient Safety

Patient Safety
Author: Institute of Medicine,Board on Health Care Services,Committee on Data Standards for Patient Safety
Publsiher: National Academies Press
Total Pages: 550
Release: 2003-12-20
ISBN 10: 0309090776
ISBN 13: 9780309090773
Language: EN, FR, DE, ES & NL

Patient Safety Book Review:

Americans should be able to count on receiving health care that is safe. To achieve this, a new health care delivery system is needed â€" a system that both prevents errors from occurring, and learns from them when they do occur. The development of such a system requires a commitment by all stakeholders to a culture of safety and to the development of improved information systems for the delivery of health care. This national health information infrastructure is needed to provide immediate access to complete patient information and decision-support tools for clinicians and their patients. In addition, this infrastructure must capture patient safety information as a by-product of care and use this information to design even safer delivery systems. Health data standards are both a critical and time-sensitive building block of the national health information infrastructure. Building on the Institute of Medicine reports To Err Is Human and Crossing the Quality Chasm, Patient Safety puts forward a road map for the development and adoption of key health care data standards to support both information exchange and the reporting and analysis of patient safety data.

Fundamentals of Clinical Data Science

Fundamentals of Clinical Data Science
Author: Pieter Kubben,Michel Dumontier,Andre Dekker
Publsiher: Springer
Total Pages: 219
Release: 2018-12-21
ISBN 10: 3319997130
ISBN 13: 9783319997131
Language: EN, FR, DE, ES & NL

Fundamentals of Clinical Data Science Book Review:

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.

Sharing Clinical Trial Data

Sharing Clinical Trial Data
Author: Institute of Medicine,Board on Health Sciences Policy,Committee on Strategies for Responsible Sharing of Clinical Trial Data
Publsiher: National Academies Press
Total Pages: 304
Release: 2015-04-20
ISBN 10: 0309316324
ISBN 13: 9780309316323
Language: EN, FR, DE, ES & NL

Sharing Clinical Trial Data Book Review:

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.

Sharing Research Data to Improve Public Health in Africa

Sharing Research Data to Improve Public Health in Africa
Author: National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on Population
Publsiher: National Academies Press
Total Pages: 102
Release: 2015-09-18
ISBN 10: 0309378125
ISBN 13: 9780309378123
Language: EN, FR, DE, ES & NL

Sharing Research Data to Improve Public Health in Africa Book Review:

Sharing research data on public health issues can promote expanded scientific inquiry and has the potential to advance improvements in public health. Although sharing data is the norm in some research fields, sharing of data in public health is not as firmly established. In March 2015, the National Research Council organized an international conference in Stellenbosch, South Africa, to explore the benefits of and barriers to sharing research data within the African context. The workshop brought together public health researchers and epidemiologists primarily from the African continent, along with selected international experts, to talk about the benefits and challenges of sharing data to improve public health, and to discuss potential actions to guide future work related to public health research data sharing. Sharing Research Data to Improve Public Health in Africa summarizes the presentations and discussions from this workshop.

Medical Data Privacy Handbook

Medical Data Privacy Handbook
Author: Aris Gkoulalas-Divanis,Grigorios Loukides
Publsiher: Springer
Total Pages: 832
Release: 2015-11-26
ISBN 10: 3319236334
ISBN 13: 9783319236339
Language: EN, FR, DE, ES & NL

Medical Data Privacy Handbook Book Review:

This handbook covers Electronic Medical Record (EMR) systems, which enable the storage, management, and sharing of massive amounts of demographic, diagnosis, medication, and genomic information. It presents privacy-preserving methods for medical data, ranging from laboratory test results to doctors’ comments. The reuse of EMR data can greatly benefit medical science and practice, but must be performed in a privacy-preserving way according to data sharing policies and regulations. Written by world-renowned leaders in this field, each chapter offers a survey of a research direction or a solution to problems in established and emerging research areas. The authors explore scenarios and techniques for facilitating the anonymization of different types of medical data, as well as various data mining tasks. Other chapters present methods for emerging data privacy applications and medical text de-identification, including detailed surveys of deployed systems. A part of the book is devoted to legislative and policy issues, reporting on the US and EU privacy legislation and the cost of privacy breaches in the healthcare domain. This reference is intended for professionals, researchers and advanced-level students interested in safeguarding medical data.

Integrating Social Care into the Delivery of Health Care

Integrating Social Care into the Delivery of Health Care
Author: National Academies of Sciences, Engineering, and Medicine,Health and Medicine Division,Board on Health Care Services,Committee on Integrating Social Needs Care into the Delivery of Health Care to Improve the Nation's Health
Publsiher: National Academies Press
Total Pages: 194
Release: 2020-01-30
ISBN 10: 0309493439
ISBN 13: 9780309493437
Language: EN, FR, DE, ES & NL

Integrating Social Care into the Delivery of Health Care Book Review:

Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health was released in September 2019, before the World Health Organization declared COVID-19 a global pandemic in March 2020. Improving social conditions remains critical to improving health outcomes, and integrating social care into health care delivery is more relevant than ever in the context of the pandemic and increased strains placed on the U.S. health care system. The report and its related products ultimately aim to help improve health and health equity, during COVID-19 and beyond. The consistent and compelling evidence on how social determinants shape health has led to a growing recognition throughout the health care sector that improving health and health equity is likely to depend â€" at least in part â€" on mitigating adverse social determinants. This recognition has been bolstered by a shift in the health care sector towards value-based payment, which incentivizes improved health outcomes for persons and populations rather than service delivery alone. The combined result of these changes has been a growing emphasis on health care systems addressing patients' social risk factors and social needs with the aim of improving health outcomes. This may involve health care systems linking individual patients with government and community social services, but important questions need to be answered about when and how health care systems should integrate social care into their practices and what kinds of infrastructure are required to facilitate such activities. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health examines the potential for integrating services addressing social needs and the social determinants of health into the delivery of health care to achieve better health outcomes. This report assesses approaches to social care integration currently being taken by health care providers and systems, and new or emerging approaches and opportunities; current roles in such integration by different disciplines and organizations, and new or emerging roles and types of providers; and current and emerging efforts to design health care systems to improve the nation's health and reduce health inequities.

Data Science and Predictive Analytics

Data Science and Predictive Analytics
Author: Ivo D. Dinov
Publsiher: Springer
Total Pages: 329
Release: 2018-04-07
ISBN 10: 3319723472
ISBN 13: 9783319723471
Language: EN, FR, DE, ES & NL

Data Science and Predictive Analytics Book Review:

Over the past decade, Big Data have become ubiquitous in all economic sectors, scientific disciplines, and human activities. They have led to striking technological advances, affecting all human experiences. Our ability to manage, understand, interrogate, and interpret such extremely large, multisource, heterogeneous, incomplete, multiscale, and incongruent data has not kept pace with the rapid increase of the volume, complexity and proliferation of the deluge of digital information. There are three reasons for this shortfall. First, the volume of data is increasing much faster than the corresponding rise of our computational processing power (Kryder’s law > Moore’s law). Second, traditional discipline-bounds inhibit expeditious progress. Third, our education and training activities have fallen behind the accelerated trend of scientific, information, and communication advances. There are very few rigorous instructional resources, interactive learning materials, and dynamic training environments that support active data science learning. The textbook balances the mathematical foundations with dexterous demonstrations and examples of data, tools, modules and workflows that serve as pillars for the urgently needed bridge to close that supply and demand predictive analytic skills gap. Exposing the enormous opportunities presented by the tsunami of Big data, this textbook aims to identify specific knowledge gaps, educational barriers, and workforce readiness deficiencies. Specifically, it focuses on the development of a transdisciplinary curriculum integrating modern computational methods, advanced data science techniques, innovative biomedical applications, and impactful health analytics. The content of this graduate-level textbook fills a substantial gap in integrating modern engineering concepts, computational algorithms, mathematical optimization, statistical computing and biomedical inference. Big data analytic techniques and predictive scientific methods demand broad transdisciplinary knowledge, appeal to an extremely wide spectrum of readers/learners, and provide incredible opportunities for engagement throughout the academy, industry, regulatory and funding agencies. The two examples below demonstrate the powerful need for scientific knowledge, computational abilities, interdisciplinary expertise, and modern technologies necessary to achieve desired outcomes (improving human health and optimizing future return on investment). This can only be achieved by appropriately trained teams of researchers who can develop robust decision support systems using modern techniques and effective end-to-end protocols, like the ones described in this textbook. • A geriatric neurologist is examining a patient complaining of gait imbalance and posture instability. To determine if the patient may suffer from Parkinson’s disease, the physician acquires clinical, cognitive, phenotypic, imaging, and genetics data (Big Data). Most clinics and healthcare centers are not equipped with skilled data analytic teams that can wrangle, harmonize and interpret such complex datasets. A learner that completes a course of study using this textbook will have the competency and ability to manage the data, generate a protocol for deriving biomarkers, and provide an actionable decision support system. The results of this protocol will help the physician understand the entire patient dataset and assist in making a holistic evidence-based, data-driven, clinical diagnosis. • To improve the return on investment for their shareholders, a healthcare manufacturer needs to forecast the demand for their product subject to environmental, demographic, economic, and bio-social sentiment data (Big Data). The organization’s data-analytics team is tasked with developing a protocol that identifies, aggregates, harmonizes, models and analyzes these heterogeneous data elements to generate a trend forecast. This system needs to provide an automated, adaptive, scalable, and reliable prediction of the optimal investment, e.g., R&D allocation, that maximizes the company’s bottom line. A reader that complete a course of study using this textbook will be able to ingest the observed structured and unstructured data, mathematically represent the data as a computable object, apply appropriate model-based and model-free prediction techniques. The results of these techniques may be used to forecast the expected relation between the company’s investment, product supply, general demand of healthcare (providers and patients), and estimate the return on initial investments.

Global Health Informatics

Global Health Informatics
Author: Heimar Marin,Eduardo Massad,Marco Antonio Gutierrez,Roberto Jaime Rodrigues,Daniel Sigulem
Publsiher: Academic Press
Total Pages: 312
Release: 2016-12-08
ISBN 10: 0128046171
ISBN 13: 9780128046173
Language: EN, FR, DE, ES & NL

Global Health Informatics Book Review:

Global Health Informatics: How Information Technology Can Change Our Lives in a Globalized World discusses the critical role of information and communication technologies in health practice, health systems management and research in increasingly interconnected societies. In a global interconnected world the old standalone institutional information systems have proved to be inadequate for patient-centered care provided by multiple providers, for the early detection and response to emerging and re-emerging diseases, and to guide population-oriented public health interventions. The book reviews pertinent aspects and successful current experiences related to standards for health information systems; digital systems as a support for decision making, diagnosis and therapy; professional and client education and training; health systems operation; and intergovernmental collaboration. Discusses how standalone systems can compromise health care in globalized world Provides information on how information and communication technologies (ICT) can support diagnose, treatment, and prevention of emerging and re-emerging diseases Presents case studies about integrated information and how and why to share data can facilitate governance and strategies to improve life conditions

The Enterprise Big Data Lake

The Enterprise Big Data Lake
Author: Alex Gorelik
Publsiher: "O'Reilly Media, Inc."
Total Pages: 224
Release: 2019-02-21
ISBN 10: 1491931507
ISBN 13: 9781491931509
Language: EN, FR, DE, ES & NL

The Enterprise Big Data Lake Book Review:

The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You’ll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book. Alex Gorelik, CTO and founder of Waterline Data, explains why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you’ll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries. Get a succinct introduction to data warehousing, big data, and data science Learn various paths enterprises take to build a data lake Explore how to build a self-service model and best practices for providing analysts access to the data Use different methods for architecting your data lake Discover ways to implement a data lake from experts in different industries

U Healthcare Monitoring Systems

U Healthcare Monitoring Systems
Author: Nilanjan Dey,Amira Ashour,Simon James Fong,Surekha Borra
Publsiher: Academic Press
Total Pages: 427
Release: 2018-09-17
ISBN 10: 0128156384
ISBN 13: 9780128156384
Language: EN, FR, DE, ES & NL

U Healthcare Monitoring Systems Book Review:

U-Healthcare Monitoring Systems: Volume One: Design and Applications focuses on designing efficient U-healthcare systems which require the integration and development of information technology service/facilities, wireless sensors technology, wireless communication tools, and localization techniques, along with health management monitoring, including increased commercialized service or trial services. These u-healthcare systems allow users to check and remotely manage the health conditions of their parents. Furthermore, context-aware service in u-healthcare systems includes a computer which provides an intelligent service based on the user’s different conditions by outlining appropriate information relevant to the user’s situation. This volume will help engineers design sensors, wireless systems and wireless communication embedded systems to provide an integrated u-healthcare monitoring system. This volume provides readers with a solid basis in the design and applications of u-healthcare monitoring systems. Provides a solid basis in the design and applications of the u-healthcare monitoring systems Illustrates the concept of the u-healthcare monitoring system and its requirements, with a specific focus on the medical sensors and wireless sensors communication Presents a multidisciplinary volume that includes different applications of the monitoring system which highlight the main features for biomedical sensor devices

Future of Patient Data

Future of Patient Data
Author: Tim Jones,Caroline Dewing
Publsiher: Createspace Independent Publishing Platform
Total Pages: 134
Release: 2018-05-07
ISBN 10: 9781718864580
ISBN 13: 1718864582
Language: EN, FR, DE, ES & NL

Future of Patient Data Book Review:

We are witnessing a growing revolution around the provision of healthcare. Much is being driven by the proliferation of medical data and the technology that supports this. As the pressures on healthcare providers continue to escalate, the better collection, management and use of more patient-specific information provides a significant opportunity for innovation and change. The Future Agenda team made this, the Future of Patient Data, the focus of our major Open Foresight project for 2017/18 - 12 discussions across 11 countries, gathering views from over 300 experts. This report shares the findings from the Future of Patient Data research project. It highlights several important emerging issues that are the source of major differences of opinion around the world. These include how to best accommodate rising data sovereignty concerns, the privatisation of health information and the growing value of health data. Some of the challenges and opportunities are technical in nature, but many are concerned with different ethical, philosophical and cultural approaches to health and how we treat the sick in society.

The Data Book

The Data Book
Author: Meredith Zozus
Publsiher: CRC Press
Total Pages: 336
Release: 2017-07-12
ISBN 10: 1351647733
ISBN 13: 9781351647731
Language: EN, FR, DE, ES & NL

The Data Book Book Review:

The Data Book: Collection and Management of Research Data is the first practical book written for researchers and research team members covering how to collect and manage data for research. The book covers basic types of data and fundamentals of how data grow, move and change over time. Focusing on pre-publication data collection and handling, the text illustrates use of these key concepts to match data collection and management methods to a particular study, in essence, making good decisions about data. The first section of the book defines data, introduces fundamental types of data that bear on methodology to collect and manage them, and covers data management planning and research reproducibility. The second section covers basic principles of and options for data collection and processing emphasizing error resistance and traceability. The third section focuses on managing the data collection and processing stages of research such that quality is consistent and ultimately capable of supporting conclusions drawn from data. The final section of the book covers principles of data security, sharing, and archival. This book will help graduate students and researchers systematically identify and implement appropriate data collection and handling methods.

New Horizons for a Data Driven Economy

New Horizons for a Data Driven Economy
Author: José María Cavanillas,Edward Curry,Wolfgang Wahlster
Publsiher: Springer
Total Pages: 303
Release: 2016-04-04
ISBN 10: 3319215698
ISBN 13: 9783319215693
Language: EN, FR, DE, ES & NL

New Horizons for a Data Driven Economy Book Review:

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.

Big Data in Radiation Oncology

Big Data in Radiation Oncology
Author: Jun Deng,Lei Xing
Publsiher: CRC Press
Total Pages: 289
Release: 2019-03-07
ISBN 10: 1351801112
ISBN 13: 9781351801119
Language: EN, FR, DE, ES & NL

Big Data in Radiation Oncology Book Review:

Big Data in Radiation Oncology gives readers an in-depth look into how big data is having an impact on the clinical care of cancer patients. While basic principles and key analytical and processing techniques are introduced in the early chapters, the rest of the book turns to clinical applications, in particular for cancer registries, informatics, radiomics, radiogenomics, patient safety and quality of care, patient-reported outcomes, comparative effectiveness, treatment planning, and clinical decision-making. More features of the book are: Offers the first focused treatment of the role of big data in the clinic and its impact on radiation therapy. Covers applications in cancer registry, radiomics, patient safety, quality of care, treatment planning, decision making, and other key areas. Discusses the fundamental principles and techniques for processing and analysis of big data. Address the use of big data in cancer prevention, detection, prognosis, and management. Provides practical guidance on implementation for clinicians and other stakeholders. Dr. Jun Deng is a professor at the Department of Therapeutic Radiology of Yale University School of Medicine and an ABR board certified medical physicist at Yale-New Haven Hospital. He has received numerous honors and awards such as Fellow of Institute of Physics in 2004, AAPM Medical Physics Travel Grant in 2008, ASTRO IGRT Symposium Travel Grant in 2009, AAPM-IPEM Medical Physics Travel Grant in 2011, and Fellow of AAPM in 2013. Lei Xing, Ph.D., is the Jacob Haimson Professor of Medical Physics and Director of Medical Physics Division of Radiation Oncology Department at Stanford University. His research has been focused on inverse treatment planning, tomographic image reconstruction, CT, optical and PET imaging instrumentations, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. Dr. Xing is on the editorial boards of a number of journals in radiation physics and medical imaging, and is recipient of numerous awards, including the American Cancer Society Research Scholar Award, The Whitaker Foundation Grant Award, and a Max Planck Institute Fellowship.

INFORMS Analytics Body of Knowledge

INFORMS Analytics Body of Knowledge
Author: James J. Cochran
Publsiher: John Wiley & Sons
Total Pages: 400
Release: 2018-09-21
ISBN 10: 1119488257
ISBN 13: 9781119488255
Language: EN, FR, DE, ES & NL

INFORMS Analytics Body of Knowledge Book Review:

Standardizes the definition and framework of analytics #2 on Book Authority’s list of the Best New Analytics Books to Read in 2019 (January 2019) We all want to make a difference. We all want our work to enrich the world. As analytics professionals, we are fortunate - this is our time! We live in a world of pervasive data and ubiquitous, powerful computation. This convergence has inspired and accelerated the development of both analytic techniques and tools and this potential for analytics to have an impact has been a huge call to action for organizations, universities, and governments. This title from Institute for Operations Research and the Management Sciences (INFORMS) represents the perspectives of some of the most respected experts on analytics. Readers with various backgrounds in analytics – from novices to experienced professionals – will benefit from reading about and implementing the concepts and methods covered here. Peer reviewed chapters provide readers with in-depth insights and a better understanding of the dynamic field of analytics The INFORMS Analytics Body of Knowledge documents the core concepts and skills with which an analytics professional should be familiar; establishes a dynamic resource that will be used by practitioners to increase their understanding of analytics; and, presents instructors with a framework for developing academic courses and programs in analytics.

Digital Infrastructure for the Learning Health System

Digital Infrastructure for the Learning Health System
Author: Institute of Medicine,Roundtable on Value and Science-Driven Health Care
Publsiher: National Academies Press
Total Pages: 336
Release: 2011-10-21
ISBN 10: 0309154162
ISBN 13: 9780309154161
Language: EN, FR, DE, ES & NL

Digital Infrastructure for the Learning Health System Book Review:

Like many other industries, health care is increasingly turning to digital information and the use of electronic resources. The Institute of Medicine's Roundtable on Value & Science-Driven Health Care hosted three workshops to explore current efforts and opportunities to accelerate progress in improving health and health care with information technology systems.