The National Academies of Sciences, Engineering, and Medicine held the workshop Applying Big Data to Address the Social Determinants of Health in Oncology on October 28â€"29, 2019, in Washington, DC. This workshop examined social determinants of health (SDOH) in the context of cancer, and considered opportunities to effectively leverage big data to improve health equity and reduce disparities. The workshop featured presentations and discussion by experts in technology, oncology, and SDOH, as well as representatives from government, industry, academia, and health care systems. This publication summarizes the presentations and discussions from the workshop.

This book provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery. Written for health care professionals and executives, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, it includes case studies that illustrate the business processes that underlie the use of big data and health analytics to improve health care delivery.

We are in the era of large-scale science. In oncology there is a huge number of data sets grouping information on cancer genomes, transcriptomes, clinical data, and more. The challenge of big data in cancer is to integrate all this diversity of data collected into a unique platform that can be analyzed, leading to the generation of readable files. The possibility of harnessing information from all the accumulated data leads to an improvement in cancer patient treatment and outcome. Solving the big data problem in oncology has multiple facets. Big data in Oncology: Impact, Challenges, and Risk Assessment brings together insights from emerging sophisticated information and communication technologies such as artificial intelligence, data science, and big data analytics for cancer management. This book focuses on targeted disease treatment using big data analytics. It provides information about the targeted treatment in oncology, challenges and application of big data in cancer therapy. Features include: • Recent developments in the fields of artificial intelligence, machine learning, medical imaging, personalized medicine, computing and data analytics for improved patient care. • Description of the application of big data with AI to discover new targeting points for cancer treatment. • Summary of several risk assessments in the field of oncology using big data. • Focus on prediction of doses in oncology using big data. The most targeted or relevant audience is academicians, research scholars, health care professionals, hospital management, pharmaceutical chemist, biomedical industry, software engineers and IT professionals.

Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data. This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians. The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in the healthcare sector is to come up with ways to provide personalized healthcare to patients by taking into account the enormous amounts of already existing data. Provides case studies that illustrate the business processes underlying the use of big data and deep learning health analytics to improve health care delivery Supplies readers with a foundation for further specialized study in clinical analysis and data management Includes links to websites, videos, articles and other online content to expand and support the primary learning objectives for each major section of the book

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.

Designed for professionals and aspiring professionals in public policy, public health, and related programs, Public Health Leadership illustrates the complexity of contemporary issues at the intersection of public health and healthcare and the compelling need to engage numerous public and private stakeholders to effectively advance population health. Offering real-world case studies and cutting-edge topics in public health and healthcare, this book will complement existing primers and introductory books in public health to help students and practitioners bridge concepts and practice. The work is divided into three parts that focus on the new role of public health departments, emerging challenges and opportunities following the enactment of the Patient Protection and Affordable Care Act (ACA), and recent trends in innovation and investment. Each chapter is practice-oriented to provide insight into the changing landscape of public health while offering practical tips based on the experiences and expertise of leading practitioners. Topics include cross-sector partnership-building, innovations in investment strategies, public health operations, performance management, advances in big data tracking, and more that address the social determinants of health and improve population health. Cases draw on a wide range of perspectives and regions, encouraging the reader, whether a professional or student, to apply the lessons learned to one’s local context.