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SPIRES-BOOKS: FIND KEYWORD MEDICAL RECORDS DATA PROCESSING *END*INIT* use /tmp/qspiwww.webspi1/23632.281 QRY 131.225.70.96 . find keyword medical records data processing ( in books using www Cover
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Call number:SPRINGER-2013-9781461474289:ONLINE Show nearby items on shelf
Title:Statistical Methods for Dynamic Treatment Regimes [electronic resource] : Reinforcement Learning, Causal Inference, and Personalized Medicine
Author(s): Bibhas Chakraborty
Erica E.M Moodie
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine. Thisvolume demonstrates thes e methods with their conceptual underpinnings and illustration through analysis of real and simulated data. These methods are immediately applicable to the practice of personalized medicine, which is a medicalparadigm that emphasizes the systematic use of individual patient information to optimize patient health care. This is the first single source to provide an overview of methodology and results gathered from journals, proceedings, andtechnical reports with the goal of orienting researchers to the fiel d. The first chapter establishes context for the statistical reader in the landscape of personalized medicine. Readers need only have familiarity with elementarycalculus, linear algebra, and basic large-sample theory to use this text. Throughout the text, authors direct readers to available code or packages in different statistical languages to facilitate implementation. In cases where codedoes not already exist, the authors provide analytic approaches in sufficient detail that any researcher with knowled ge of statistical programming could implement the methods from scratch. This will be an important volume for a widerange of researchers, including statisticians, epidemiologists, medical researchers, and machine learning researchers interested in medical applications. Advanced graduate students in statistics and biostatistics will also findmaterial in Statistical Methods for Dynamic Treatment Regimes to be a critical part of their studies
Note:Springer eBooks
Contents:Introduction
The Data: Observational Studies and Sequentially Randomized Trials
Statistical Reinforcement Learning
Estimation of Optimal DTRs by Modeling Contrasts of Conditional Mean Outcomes
Estimation of Optimal DTRs by Directly Modeling Regimes
G
computation: Parametric Estimation of Optimal DTRs
Estimation DTRs for Alternative Outcome Types
Inference and Non
regularity
Additional Considerations and Final Thoughts
Glossary
Index
References
ISBN:9781461474289
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Medical records Data processing
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Call number:SPRINGER-2012-9781461441335:ONLINE Show nearby items on shelf
Title:Optimization and Data Analysis in Biomedical Informatics [electronic resource]
Author(s): Panos M Pardalos
Thomas F Coleman
Petros Xanthopoulos
Date:2012
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This volume covers some of the topics that are related to the rapidly growing field of biomedical informatics. In June 1112, 2010 a workshop entitled Optimization and Data Analysis in Biomedical Informatics was organizedat The Fields Institute. Follo wing this event, invited contributions were gathered based on the talks presented at the workshop, and additional invited chapters weresolicited from leading experts. In this publication, the authorsshare their expertise in the form of state-of-the-art re search and review chapters, bringing together researchers from different disciplines andemphasizing the value of mathematical methods in the areas of clinical sciences. Thiswork is targeted to applied mathematicians, computer scientists, industrial engine ers, and clinical scientists who are interested in exploring emerging and fascinating interdisciplinary topics of research. It is designed to furtherstimulate and enhance fruitful collaborations between scientists from different disciplines
Note:Springer eBooks
Contents:Preface
Novel Biclustering Methods for Re
Ordering Data Matrices (P.A. DiMaggio Jr., A. Subramani, C.A. Floudas)
Clustering Time Series Data with Distance Matrices (O. eref, W.A. Chaovalitwongse)
Mathematical Models of Supervised Learning and Application to Medical Diagnosis (R. De Asmundis, M.R. Guarracino)
Predictive Model for Early Detection of Mild Cognitive Impairment and Alzheimers Disease (E.K. Lee, T
L. Wu, F. Goldstein, A. Levey)
Strategies for Bias Reduction in Estimation of Marginal Means with Data Missing at Random (B. Chen, R.J. Cook)
Cardiovascular Informa
ISBN:9781461441335
Series:e-books
Series:SpringerLink (Online service)
Series:Fields Institute Communications, 1069-5265 : v63
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Biochemical engineering , Medical records Data processing , Data mining , Mathematical optimization
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Call number:SPRINGER-2012-9781461421078:ONLINE Show nearby items on shelf
Title:Data Mining for Biomarker Discovery [electronic resource]
Author(s): Panos M Pardalos
Petros Xanthopoulos
Michalis Zervakis
Date:2012
Publisher:Boston, MA : Springer US
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Data Mining for Biomarker Discovery is designed to motivate collaboration and discussion among various disciplines and will be of interest to students and researchers in engineering, computer science, applied mathematics,medicine, and anyone interest ed in the interdisciplinary application of data mining techniques. Biomarker discovery is an important area of biomedical research that can lead to significant breakthroughs in disease analysis and targetedtherapy. Moreover, the discovery and management o f new biomarkers is a challenging and attractive problem in the emerging field of biomedical informatics. This volume is acollection of state-of-the-artresearch from selectparticipants of the International Conference on Biomedical Data and Knowledge Minin g: Towards Biomarker Discovery, held July 7-9, 2010 in Chania, Greece. Contributions focus on biomarker data integration, information retrievalmethods, and statistical machine learning techniques, all presented with new results, models, and algorithms
Note:Springer eBooks
Contents:Preface
1. Data Mining Strategies Applied in Brain Injury Models (S. Mondello, F. Kobeissy, I. Fingers, Z. Zhang, R.L. Hayes, K.K.W. Wang)
Application of Decomposition Methods in the Filtering of Event Related Potentials (K. Michalopoulos, V. Iordanidou, M. Zervakis)
3. EEG Features as Biomarkers for Discrimination of Pre
ictal states (A. Tsimpiris, D. Kugiumtzis)
4. Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Non
epileptic Seizure and Complex Partial Seizure Patients (J.H. Chien, D
S. Shiau, J.C. Sackellares, J.J. Halford, K.M. Kelly, P.M. Pardalos)
ISBN:9781461421078
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Optimization and Its Applications, 1931-6828 : v65
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Biochemical engineering , Medical records Data processing , Data mining
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Call number:HF5738.A32::2008 Show nearby items on shelf
Title:Implementing electronic document and record management systems
Author(s): Azad Adam
Date:2008
Publisher:Auerbach Publications
Contents:The History and Background of EDRMS, Fundamentals of EDRMS, Complying with Standards and Legislation, Creating Electronic Document Types, Creating the Folder Structure, Search and Retrieval, Integrating Workflow, Email Management, Records Management and Records Management Policies, User Interfaces, Mobile Working and Remote Access, Scanning Historical Documents and Records, The Business Case, The Functional Requirements, The Technical Specification, EDRMS Software Platforms, Hardware Considerations, Managing the Cultural Change of EDRMS, The On-going Nature of the Project
ISBN:9780849380594
Keywords: Electronic filing systems , Business records Data processing Management , Public records Data processing Management , Medical records Data processing Management , Records Management Data processing , Electronic records Management , Text processing (Computer science)
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Location: MAIN

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