Описание: Medical informatics lies at the intersection of computer science and medicine, and understanding critical aspects of both fields provides for more proficient practitioners. Biomedical Informatics: An Introduction to Information Systems and Software in Medicine and Health supplies a cohesive narrative of the multidisciplinary concepts linking the field.This complete medical informatics textbook begins by reviewing the IT aspects of informatics, including systems architecture, electronic health records, interoperability, privacy and security, cloud computing, mobile healthcare, imaging, data capture, and design issues. Next, the text provides case studies that demonstrate the roll out of electronic health records (EHRs) in hospitals.The third section incorporates four anatomy and physiology lectures that focus on the physiological basis behind data captured in EHRs. Examples include detailed descriptions of the heart and electrical systems, lungs and alveoli, and oxygen exchange.The book includes a primer on the theoretical concepts that underpin the science behind medical informatics, including an Anatomy & Physiology Essentials guide. It also contains a tutorial on application development to help students understand the tools for improving user interfaces for EHRs on mobile platforms.The author uses a student-friendly organizational structure that supplies students with a clear demarcation between essential and optional material. The text supplies clear delineation between Level I, the basic concepts every biomedical informatics professional needs to master; Level II, applied concepts and examples; and Level III, advanced topics. This format allows undergraduate and graduate instructors and professionals in the field to focus quickly on the essential topics, and if interested, delve into Level III advanced topics.The book includes links to documents and standards sources so students can explore each idea described in more detail. Instructor’s manual, solutions manual, videos, figure slides, and lecture slides are available upon qualified course adoption.
Автор: Houston, Susan Bove, Lisa Anne Название: Project Management for Healthcare Informatics ISBN: 0387736824 ISBN-13(EAN): 9780387736822 Издательство: Springer Рейтинг: Цена: 10798.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Through its use of real clinical examples, this book provides an explanation of the project management process tailored for nurses. Coverage includes the tools available to successfully complete each phase of the project management process and advance the project life cycle.
Автор: Sundaram, Rangarajan K. Название: A First Course in Optimization Theory ISBN: 0521497701 ISBN-13(EAN): 9780521497701 Издательство: Cambridge Academ Рейтинг: Цена: 6811.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, first published in 1996, introduces students to optimization theory and its use in economics and allied disciplines.
Автор: Dong Xu; May D. Wang; Fengfeng Zhou; Yunpeng Cai Название: Health Informatics Data Analysis ISBN: 3319449796 ISBN-13(EAN): 9783319449791 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1 Electrocardiogram.- 2 EEG visualization and analysis techniques.- 3 Big health data mining.- 4 Computational infrastructure for tele-health.- 5 Identification and Functional Annotation of lncRNAs in human disease.- 6 Metabolomics characterization of human diseases.- 7 Metagenomics for Monitoring Environmental Biodiversity: Challenges, Progress, and Opportunities.- 8 Global nonlinearfitness function for protein structures.- 9 Clinical Assessment of Disease Risk Factors Using SNP Data and Bayesian Methods.- 10 Imaging genetics: information fusion and association techniques between biomedical images and genetic factors.
Автор: Biehl Название: Data Warehousing for Biomedical Informatics ISBN: 1482215217 ISBN-13(EAN): 9781482215212 Издательство: Taylor&Francis Рейтинг: Цена: 19906.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Data Warehousing for Biomedical Informatics is a step-by-step how-to guide for designing and building an enterprise-wide data warehouse across a biomedical or healthcare institution, using a four-iteration lifecycle and standardized design pattern. It enables you to quickly implement a fully-scalable generic data architecture that supports your organization's clinical, operational, administrative, financial, and research data. By following the guidelines in this book, you will be able to successfully progress through the Alpha, Beta, and Gamma versions, plus fully implement your first production release in about a year.
The Alpha version allows you to implement just enough of the basic design pattern to illustrate its core capabilities while loading a small sampling of limited data for demonstration purposes. This provides an easy way for everyone involved to visualize the new warehouse paradigm by actually examining a core subset of the working system. You can finish the Alpha version, also referred to as the proof-of-concept, in as little as 3-4 weeks.
The Beta version, which can be completed in about 2-3 months, adds required functionality and much more data. It allows you to get the full warehouse up and running quickly, in order to facilitate longer-term planning, user and support team training, and setup of the operational environment. The Gamma version, which is a fully-functional system-though still lacking data-can be implemented in about 3-4 months. About one year after starting, you will be ready to launch Release 1.0 as a complete and secure data warehouse.
Описание: Knowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions.- Visual Data Mining: Effective Exploration of the Biological Universe.- Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining.- On the Generation of Point Cloud Data Sets: Step One in the Knowledge Discovery Process.- Adapted Features and Instance Selection for Improving Co-training.- Knowledge Discovery and Visualization of Clusters for Erythromycin Related Adverse Events in the FDA Drug Adverse Event Reporting System.- On Computationally-Enhanced Visual Analysis of Heterogeneous Data and Its Application in Biomedical Informatics.- A Policy-Based Cleansing and Integration Framework for Labour and Healthcare Data.- Interactive Data Exploration Using Pattern Mining.- Resources for Studying Statistical Analysis of Biomedical Data and R.- A Kernel-Based Framework for Medical Big-Data Analytics.- On Entropy-Based Data Mining.- Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure.- Multi-touch Graph-Based Interaction for Knowledge Discovery on Mobile Devices: State-of-the-Art and Future Challenges.- Intelligent Integrative Knowledge Bases: Bridging Genomics, Integrative Biology and Translational Medicine.- Biomedical Text Mining: State-of-the-Art, Open Problems and Future Challenges.- Protecting Anonymity in Data-Driven Biomedical Science.- Biobanks - A Source of Large Biological Data Sets: Open Problems and Future Challenges.- On Topological Data Mining.
Demystifies Biomedical and Biological Big Data Analyses
Big Data Analysis for Bioinformatics and Biomedical Discoveries provides a practical guide to the nuts and bolts of Big Data, enabling you to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implement personalized genomic medicine. Contributing to the NIH Big Data to Knowledge (BD2K) initiative, the book enhances your computational and quantitative skills so that you can exploit the Big Data being generated in the current omics era.
The book explores many significant topics of Big Data analyses in an easily understandable format. It describes popular tools and software for Big Data analyses and explains next-generation DNA sequencing data analyses. It also discusses comprehensive Big Data analyses of several major areas, including the integration of omics data, pharmacogenomics, electronic health record data, and drug discovery.
Accessible to biologists, biomedical scientists, bioinformaticians, and computer data analysts, the book keeps complex mathematical deductions and jargon to a minimum. Each chapter includes a theoretical introduction, example applications, data analysis principles, step-by-step tutorials, and authoritative references.
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