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Author: Classification Society. Meeting
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 524
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Book Description
This work contains a selection of papers presented at the meeting. The subjects covered include: Data analysis: Methods of scaling, Loglinear models, Correspondence analysis, Pattern recognition and discrimination, Analysis and aggregation of discrete structures, Measures of similarity and association. Numerical classification: Clustering methods, Robustness of methods, Fuzzy clustering, Statistical models. Concept analysis: Construction and reconstruction of concepts, Theories of characteristics and of definitions, Impact on artificial intelligence. Indexing languages and terminologies as information resources: Classification systems, Thesauri, Conceptual structure utilization, Identification of analogies. Software tools (especially on microcomputers): Availability of programs, Interfaces to data base systems, Information retrieval systems, Method base systems, Graphical representation, Comparisons of algorithms. Applications of classification examined here include economics, business administration, natural sciences, social science and humanities, chemistry research, library science, and linguistics. Contributors: P. Arabie, I. Balderjahn, P.M. Bentler, H.-H. Bock, I.
Author: Classification Society. Meeting
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 524
Get Book Here
Book Description
This work contains a selection of papers presented at the meeting. The subjects covered include: Data analysis: Methods of scaling, Loglinear models, Correspondence analysis, Pattern recognition and discrimination, Analysis and aggregation of discrete structures, Measures of similarity and association. Numerical classification: Clustering methods, Robustness of methods, Fuzzy clustering, Statistical models. Concept analysis: Construction and reconstruction of concepts, Theories of characteristics and of definitions, Impact on artificial intelligence. Indexing languages and terminologies as information resources: Classification systems, Thesauri, Conceptual structure utilization, Identification of analogies. Software tools (especially on microcomputers): Availability of programs, Interfaces to data base systems, Information retrieval systems, Method base systems, Graphical representation, Comparisons of algorithms. Applications of classification examined here include economics, business administration, natural sciences, social science and humanities, chemistry research, library science, and linguistics. Contributors: P. Arabie, I. Balderjahn, P.M. Bentler, H.-H. Bock, I.
Author: Geoffrey C. Bowker
Publisher: MIT Press
ISBN: 0262522950
Category : Science
Languages : en
Pages : 390
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Book Description
A revealing and surprising look at how classification systems can shape both worldviews and social interactions. What do a seventeenth-century mortality table (whose causes of death include "fainted in a bath," "frighted," and "itch"); the identification of South Africans during apartheid as European, Asian, colored, or black; and the separation of machine- from hand-washables have in common? All are examples of classification—the scaffolding of information infrastructures. In Sorting Things Out, Geoffrey C. Bowker and Susan Leigh Star explore the role of categories and standards in shaping the modern world. In a clear and lively style, they investigate a variety of classification systems, including the International Classification of Diseases, the Nursing Interventions Classification, race classification under apartheid in South Africa, and the classification of viruses and of tuberculosis. The authors emphasize the role of invisibility in the process by which classification orders human interaction. They examine how categories are made and kept invisible, and how people can change this invisibility when necessary. They also explore systems of classification as part of the built information environment. Much as an urban historian would review highway permits and zoning decisions to tell a city's story, the authors review archives of classification design to understand how decisions have been made. Sorting Things Out has a moral agenda, for each standard and category valorizes some point of view and silences another. Standards and classifications produce advantage or suffering. Jobs are made and lost; some regions benefit at the expense of others. How these choices are made and how we think about that process are at the moral and political core of this work. The book is an important empirical source for understanding the building of information infrastructures.
Author: Charu C. Aggarwal
Publisher: CRC Press
ISBN: 1498760589
Category : Business & Economics
Languages : en
Pages : 710
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Book Description
Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlyi
Author: U. S. Department of Health and Human Services
Publisher: CreateSpace
ISBN: 9781484077146
Category : Medical
Languages : en
Pages : 108
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Book Description
The internal validity of a study reflects the extent to which the design and conduct of the study have prevented bias(es). One of the key steps in a systematic review is assessment of a study's internal validity, or potential for bias. This assessment serves to: (1) identify the strengths and limitations of the included studies; (2) investigate, and potentially explain heterogeneity in findings across different studies included in a systematic review; and (3) grade the strength of evidence for a given question. The risk of bias assessment directly informs one of four key domains considered when assessing the strength of evidence. With the increase in the number of published systematic reviews and development of systematic review methodology over the past 15 years, close attention has been paid to the methods for assessing internal validity. Until recently this has been referred to as “quality assessment” or “assessment of methodological quality.” In this context “quality” refers to “the confidence that the trial design, conduct, and analysis has minimized or avoided biases in its treatment comparisons.” To facilitate the assessment of methodological quality, a plethora of tools has emerged. Some of these tools were developed for specific study designs (e.g., randomized controlled trials (RCTs), cohort studies, case-control studies), while others were intended to be applied to a range of designs. The tools often incorporate characteristics that may be associated with bias; however, many tools also contain elements related to reporting (e.g., was the study population described) and design (e.g., was a sample size calculation performed) that are not related to bias. The Cochrane Collaboration recently developed a tool to assess the potential risk of bias in RCTs. The Risk of Bias (ROB) tool was developed to address some of the shortcomings of existing quality assessment instruments, including over-reliance on reporting rather than methods. Several systematic reviews have catalogued and critiqued the numerous tools available to assess methodological quality, or risk of bias of primary studies. In summary, few existing tools have undergone extensive inter-rater reliability or validity testing. Moreover, the focus of much of the tool development or testing that has been done has been on criterion or face validity. Therefore it is unknown whether, or to what extent, the summary assessments based on these tools differentiate between studies with biased and unbiased results (i.e., studies that may over- or underestimate treatment effects). There is a clear need for inter-rater reliability testing of different tools in order to enhance consistency in their application and interpretation across different systematic reviews. Further, validity testing is essential to ensure that the tools being used can identify studies with biased results. Finally, there is a need to determine inter-rater reliability and validity in order to support the uptake and use of individual tools that are recommended by the systematic review community, and specifically the ROB tool within the Evidence-based Practice Center (EPC) Program. In this project we focused on two tools that are commonly used in systematic reviews. The Cochrane ROB tool was designed for RCTs and is the instrument recommended by The Cochrane Collaboration for use in systematic reviews of RCTs. The Newcastle-Ottawa Scale is commonly used for nonrandomized studies, specifically cohort and case-control studies.
Author: Khuntia, Jiban
Publisher: IGI Global
ISBN: 1799823113
Category : Medical
Languages : en
Pages : 322
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Book Description
Business intelligence supports managers in enterprises to make informed business decisions in various levels and domains such as in healthcare. These technologies can handle large structured and unstructured data (big data) in the healthcare industry. Because of the complex nature of healthcare data and the significant impact of healthcare data analysis, it is important to understand both the theories and practices of business intelligence in healthcare. Theory and Practice of Business Intelligence in Healthcare is a collection of innovative research that introduces data mining, modeling, and analytic techniques to health and healthcare data; articulates the value of big volumes of data to health and healthcare; evaluates business intelligence tools; and explores business intelligence use and applications in healthcare. While highlighting topics including digital health, operations intelligence, and patient empowerment, this book is ideally designed for healthcare professionals, IT consultants, hospital directors, data management staff, data analysts, hospital administrators, executives, managers, academicians, students, and researchers seeking current research on the digitization of health records and health systems integration.
Author: Krzysztof Jajuga
Publisher: Springer Nature
ISBN: 3030523489
Category : Business & Economics
Languages : en
Pages : 334
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Book Description
This volume gathers peer-reviewed contributions on data analysis, classification and related areas presented at the 28th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2019, held in Szczecin, Poland, on September 18–20, 2019. Providing a balance between theoretical and methodological contributions and empirical papers, it covers a broad variety of topics, ranging from multivariate data analysis, classification and regression, symbolic (and other) data analysis, visualization, data mining, and computer methods to composite measures, and numerous applications of data analysis methods in economics, finance and other social sciences. The book is intended for a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions.
Author: Rik Das
Publisher: CRC Press
ISBN: 1000280470
Category : Computers
Languages : en
Pages : 197
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Book Description
Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB® codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/
Author: Karimi, Hassan A.
Publisher: IGI Global
ISBN: 1591409969
Category : Technology & Engineering
Languages : en
Pages : 517
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Book Description
"This book discusses the complete range of contemporary research topics such as computer modeling, geometry, geoprocessing, and geographic information systems"--Provided by publisher.
Author: Solanki, Arun
Publisher: IGI Global
ISBN: 1522596453
Category : Computers
Languages : en
Pages : 674
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Book Description
As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309284740
Category : Medical
Languages : en
Pages : 179
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Book Description
In 2006 the National Institutes of Health (NIH) established the Clinical and Translational Science Awards (CTSA) Program, recognizing the need for a new impetus to encourage clinical and translational research. At the time it was very difficult to translate basic and clinical research into clinical and community practice; making it difficult for individual patients and communities to receive its benefits. Since its creation the CTSA Program has expanded, with 61 sites spread across the nation's academic health centers and other institutions, hoping to provide catalysts and test beds for policies and practices that can benefit clinical and translation research organizations throughout the country. The NIH contracted with the Institute of Medicine (IOM) in 2012 to conduct a study to assess and provide recommendations on appropriateness of the CTSA Program's mission and strategic goals and whether changes were needed. The study was also address the implementation of the program by the National Center for Advancing Translational Sciences (NCATS) while exploring the CTSA's contributions in the acceleration of the development of new therapeutics. A 13-member committee was established to head this task; the committee had collective expertise in community outreach and engagement, public health and health policy, bioethics, education and training, pharmaceutical research and development, program evaluation, clinical and biomedical research, and child health research. The CTSA Program at NIH: Opportunities for Advancing Clinical and Translational Research is the result of investigations into previous program evaluations and assessments, open-session meetings and conference class, and the review of scientific literature. Overall, the committee believes that the CTSA Program is significant to the advancement of clinical and translational research through its contributions. The Program would benefit from a variety of revisions, however, to make it more efficient and effective.
