Foraging Theory Applied to Medical Information Searching


Book Description

Workload and other constraints prevent General Practitioners from accessing medical evidence for clinical decisions. This problem was studied in New Zealand GPs using Optimal Foraging Theory developed in ecology. GPs' information search strategies were modelled as sequential steps associated with costs and benefits measured from logbooks of actual searches. By consulting the most profitable sources, switching sources when unsuccessful, and double checking, GPs seem close to an optimal trade-off between maximizing search success and information reliability, and minimizing searching time. Subsidised training in information searching and provision of a literature search service are two inferred avenues to access medical evidence.




Information Foraging Theory


Book Description

Peter Pirolli covers information foraging theory (IFT), a theory in adaptive information interaction. IFT analyses what people do to make sense of the huge amount of information available on the Internet and how they navigate it.




Health Informatics


Book Description

Health Informatics: An Interprofessional Approach was awarded first place in the 2013 AJN Book of the Year Awards in the Information Technology/Informatics category. Get on the cutting edge of informatics with Health Informatics, An Interprofessional Approach. Covering a wide range of skills and systems, this unique title prepares you for work in today's technology-filled clinical field. Topics include clinical decision support, clinical documentation, provider order entry systems, system implementation, adoption issues, and more. Case studies, abstracts, and discussion questions enhance your understanding of these crucial areas of the clinical space. 31 chapters written by field experts give you the most current and accurate information on continually evolving subjects like evidence-based practice, EHRs, PHRs, disaster recovery, and simulation. Case studies and attached discussion questions at the end of each chapter encourage higher level thinking that you can apply to real world experiences. Objectives, key terms and an abstract at the beginning of each chapter provide an overview of what each chapter will cover. Conclusion and Future Directions section 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 your understanding of the subject covered.




Health Informatics - E-Book


Book Description

Health Informatics: An Interprofessional Approach was awarded first place in the 2013 AJN Book of the Year Awards in the Information Technology/Informatics category. Get on the cutting edge of informatics with Health Informatics, An Interprofessional Approach. Covering a wide range of skills and systems, this unique title prepares you for work in today’s technology-filled clinical field. Topics include clinical decision support, clinical documentation, provider order entry systems, system implementation, adoption issues, and more. Case studies, abstracts, and discussion questions enhance your understanding of these crucial areas of the clinical space. 31 chapters written by field experts give you the most current and accurate information on continually evolving subjects like evidence-based practice, EHRs, PHRs, disaster recovery, and simulation. Case studies and attached discussion questions at the end of each chapter encourage higher level thinking that you can apply to real world experiences. Objectives, key terms and an abstract at the beginning of each chapter provide an overview of what each chapter will cover. Conclusion and Future Directions section 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 your understanding of the subject covered.










Mathematical Ecology


Book Description

There isprobably no more appropriate location to hold a course on mathematical ecology than Italy, the countryofVito Volterra, a founding father ofthe subject. The Trieste 1982Autumn Course on Mathematical Ecology consisted of four weeksofvery concentrated scholasticism and aestheticism. The first weeks were devoted to fundamentals and principles ofmathematicalecology. A nucleusofthe material from the lectures presented during this period constitutes this book. The final week and a half of the Course was apportioned to the Trieste Research Conference on Mathematical Ecology whose proceedings have been published as Volume 54, Lecture Notes in Biomathematics, Springer-Verlag. The objectivesofthe first portionofthe course wereambitious and, probably, unattainable. Basic principles of the areas of physiological, population, com munitY, and ecosystem ecology that have solid ecological and mathematical foundations were to be presented. Classical terminology was to be introduced, important fundamental topics were to be developed, some past and some current problems of interest were to be presented, and directions for possible research were to be provided. Due to time constraints, the coverage could not be encyclopedic;many areas covered already have merited treatises of book length. Consequently, preliminary foundation material was covered in some detail, but subject overviewsand area syntheseswerepresented when research frontiers were being discussed. These lecture notes reflect this course philosophy.




Hidden Markov Models for Time Series


Book Description

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data




Applications of Big Data in Healthcare


Book Description

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




Exploratory Search


Book Description

As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model supported by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world. Table of Contents: Introduction / Defining Exploratory Search / Related Work / Features of Exploratory Search Systems / Evaluation of Exploratory Search Systems / Future Directions and concluding Remarks