Big Data and Analytics for Infectious Disease Research, Operations, and Policy PDF Download

Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030945011X
Category : Medical
Languages : en
Pages : 99

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Book Description
With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time. With a wide range of data available for analysis, decision-making and policy-making processes could be improved. While there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop.

Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309450144
Category : Medical
Languages : en
Pages : 99

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Book Description
With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time. With a wide range of data available for analysis, decision-making and policy-making processes could be improved. While there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop.

Author: Sunit K. Singh
Publisher: Springer
ISBN: 3030030539
Category : Medical
Languages : en
Pages : 332

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Book Description
This first volume of a two-volume set describes general aspects, such as the historical view on the topic, the role of information distribution and preparedness of health-care systems and preparedness in emergency cases. Part two describes and discusseses in detail the pathogens and toxins that are potentially used for biological attacks. As such, the book is a valuable resource for faculties engaged in molecular biology, genetic engineering, neurology, biodefense, biosafety & biosecurity, virology, and infectious disease programs, as well as professional medical research organizations.

Author: Public Responsibility in Medicine & Research (PRIM&R),
Publisher: Jones & Bartlett Learning
ISBN: 1284235521
Category : Medical
Languages : en
Pages : 1113

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Book Description
Institutional Review Board (IRB) members and oversight personnel face challenges with research involving new technology, management of big data, globalization of research, and more complex federal regulations. Institutional Review Board: Management and Function, Third Edition provides everything IRBs and administrators need to know about efficiently managing and effectively operating a modern and compliant system of protecting human research subjects. This trusted reference manual has been extensively updated to reflect the 2018 revisions to the Federal Policy for the Protection of Human Subjects (Common Rule). An essential resource for both seasoned and novice IRB administrators and members, Institutional Review Board: Management and Function provides comprehensive and understandable interpretations of the regulations, clear descriptions of the ethical principles on which the regulations are based, and practical step-by-step guidance for effectively implementing regulatory oversight.

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: Nkuchia M. M'ikanatha
Publisher: John Wiley & Sons
ISBN: 1118543521
Category : Medical
Languages : en
Pages : 1139

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Book Description
This fully updated edition of Infectious Disease Surveillance is for frontline public health practitioners, epidemiologists, and clinical microbiologists who are engaged in communicable disease control. It is also a foundational text for trainees in public health, applied epidemiology, postgraduate medicine and nursing programs. The second edition portrays both the conceptual framework and practical aspects of infectious disease surveillance. It is a comprehensive resource designed to improve the tracking of infectious diseases and to serve as a starting point in the development of new surveillance systems. Infectious Disease Surveillance includes over 45 chapters from over 100 contributors, and topics organized into six sections based on major themes. Section One highlights the critical role surveillance plays in public health and it provides an overview of the current International Health Regulations (2005) in addition to successes and challenges in infectious disease eradication. Section Two describes surveillance systems based on logical program areas such as foodborne illnesses, vector-borne diseases, sexually transmitted diseases, viral hepatitis healthcare and transplantation associated infections. Attention is devoted to programs for monitoring unexplained deaths, agents of bioterrorism, mass gatherings, and disease associated with international travel. Sections Three and Four explore the uses of the Internet and wireless technologies to advance infectious disease surveillance in various settings with emphasis on best practices based on deployed systems. They also address molecular laboratory methods, and statistical and geospatial analysis, and evaluation of systems for early epidemic detection. Sections Five and Six discuss legal and ethical considerations, communication strategies and applied epidemiology-training programs. The rest of the chapters offer public-private partnerships, as well lessons from the 2009-2010 H1N1 influenza pandemic and future directions for infectious disease surveillance.

Author: Debabrata Samanta
Publisher: CRC Press
ISBN: 1000550427
Category : Computers
Languages : en
Pages : 275

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Book Description
With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

Author: Anand J. Kulkarni
Publisher: Springer Nature
ISBN: 3030316726
Category : Technology & Engineering
Languages : en
Pages : 193

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Book Description
This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.

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: Lynda R. Hardy
Publisher: Elsevier Health Sciences
ISBN: 0323846475
Category : Medical
Languages : en
Pages : 568

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Book Description
**American Journal of Nursing (AJN) Book of the Year Awards, 1st Place in Informatics, 2023** **Selected for Doody's Core Titles® 2024 in Informatics** Learn how information technology intersects with today's health care! Health Informatics: An Interprofessional Approach, 3rd Edition, follows the tradition of expert informatics educators Ramona Nelson and Nancy Staggers with new lead author, Lynda R. Hardy, to prepare you for success in today's technology-filled healthcare practice. Concise coverage includes information systems and applications, such as electronic health records, clinical decision support, telehealth, mHealth, ePatients, and social media tools, as well as system implementation. New to this edition are topics that include analytical approaches to health informatics, increased information on FHIR and SMART on FHIR, and the use of health informatics in pandemics. - Chapters written by experts in the field provide the most current and accurate information on continually evolving subjects like evidence-based practice, EHRs, PHRs, mobile health, disaster recovery, and simulation. - Objectives, key terms, and an abstract at the beginning of each chapter provide an overview of what each chapter will cover. - Case studies and discussion questions at the end of each chapter encourage higher-level thinking that can be applied to real world experiences. - Conclusion and Future Directions discussion at the end of each chapter reinforces topics and expands on how the topic will continue to evolve. - Open-ended discussion questions at the end of each chapter enhance students' understanding of the subject covered. - mHealth chapter discusses all relevant aspects of mobile health, including global growth, new opportunities in underserved areas, governmental regulations on issues such as data leaking and mining, implications of patient-generated data, legal aspects of provider monitoring of patient-generated data, and increased responsibility by patients. - Important content, including FDA- and state-based regulations, project management, big data, and governance models, prepares students for one of nursing's key specialty areas. - UPDATED! Chapters reflect the current and evolving practice of health informatics, using real-life healthcare examples to show how informatics applies to a wide range of topics and issues. - NEW! Strategies to promote healthcare equality by freeing algorithms and decision-making from implicit and explicit bias are integrated where applicable. - NEW! The latest AACN domains are incorporated throughout to support BSN, Master's, and DNP programs. - NEW! Greater emphasis on the digital patient and the partnerships involved, including decision-making.