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Effective administration of libraries is a crucial part of delivering library services to the public. To develop and implement best practices, librarians must be aware and informed of the recent advances in library administration. Library Science and Administration: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source for the latest scholarly material on trends, techniques, and management of libraries and examines the benefits and challenges of library administration. Highlighting a range of pertinent topics such as digital libraries, information sciences, and academic libraries, this multi-volume book is ideally designed for academicians, researchers, practitioners, and librarians seeking current research on library science and administration.
This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.
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
In a world of earthquakes, tsunamis, and terrorist attacks, emergency response plans are crucial to solving problems, overcoming challenges, and restoring and improving communities that have been affected by these catastrophic events. Although the necessity for quick and efficient aid is understood, researchers and professionals continue to strive for the best practices and methodologies to properly handle such significant events. Emergency and Disaster Management: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest research on the theoretical and practical components of initiating crisis management and emergency response. Highlighting a range of topics such as preparedness and assessment, aid and relief, and the integration of smart technologies, this multi-volume book is designed for emergency professionals, policy makers, practitioners, academicians, and researchers interested in all aspects of disaster, crisis, and emergency studies.
Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.
This is the 68th volume (supplement 31) in a series which examines library and information science.
Supporting tomorrow’s doctors involves preparing them for the technologies that will be available to them. 3D printing is one such technology that is becoming more abundant in health care settings and is similarly a technology libraries are embracing as a new service offering for their communities. 3D Printing in Medical Libraries: A Crash Course in Supporting Innovation in Health Care will provide librarians interested in starting or enhancing a 3D printing service an overview of 3D printing, highlight legal concerns, discuss 3D printing in libraries through a literature review, review survey results on 3D printing services in health sciences and medical libraries, and offer case studies of health sciences and medical libraries currently 3D printing. Additionally, resources for finding medically related models for printing and tips of how to search for models online is also provided, along with resources for creating 3D models from DICOM. Common print problems and troubleshooting tips are also highlighted and lastly, marketing and outreach opportunities are discussed. Herron presents the nitty-gritty of 3D printing without getting too technical, and a wealth of recommended resources is provided to support librarians wishing to delve further into 3D printing. Design thinking and the Maker Movement is also discussed to promote a holistic service offering that supports users not only with the service but the skills to best use the service. Readers will finish the book with a better sense of direction for 3D printing in health sciences and medical libraries and have a guide to establishing or enhancing a 3D printing in their library. This book appeals to health sciences libraries and librarians looking to start a 3D printing service or understand the 3D printing space as it relates to medical education, practice, and research. It serves as: a field guide for starting a new library service a primer for meeting the information needs of medical faculty, staff, and students a useful reference for a deep dive into this space by librarians who are already actively carrying out some of the kinds of work described herein
Computational Biology for Stem Cell Research is an invaluable guide for researchers as they explore HSCs and MSCs in computational biology. With the growing advancement of technology in the field of biomedical sciences, computational approaches have reduced the financial and experimental burden of the experimental process. In the shortest span, it has established itself as an integral component of any biological research activity. HSC informatics (in silico) techniques such as machine learning, genome network analysis, data mining, complex genome structures, docking, system biology, mathematical modeling, programming (R, Python, Perl, etc.) help to analyze, visualize, network constructions, and protein-ligand or protein-protein interactions. This book is aimed at beginners with an exact correlation between the biomedical sciences and in silico computational methods for HSCs transplantation and translational research and provides insights into methods targeting HSCs properties like proliferation, self-renewal, differentiation, and apoptosis. - Modeling Stem Cell Behavior: Explore stem cell behavior through animal models, bridging laboratory studies to real-world clinical allogeneic HSC transplantation (HSCT) scenarios. - Bioinformatics-Driven Translational Research: Navigate a path from bench to bedside with cutting-edge bioinformatics approaches, translating computational insights into tangible advancements in stem cell research and medical applications. - Interdisciplinary Resource: Discover a single comprehensive resource catering to biomedical sciences, life sciences, and chemistry fields, offering essential insights into computational tools vital for modern research.