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Intelligent Patient Management

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Cover of 'Intelligent Patient Management'

Table of Contents

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    Book Overview
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    Chapter 1 Why Nosokinetics? Measuring and Modelling the Process of Care
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    Chapter 2 Toward a Decision Support Tool for Emergency Networks in France
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    Chapter 3 Length of Stay-Based Clustering Methods for Patient Grouping
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    Chapter 4 Machine Learning and Statistical Approaches to Support the Discrimination of Neuro-degenerative Diseases Based on Gait Analysis
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    Chapter 5 Privacy-Preserving Fuzzy Matching Using a Public Reference Table
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    Chapter 6 Methodological Approach and Software Tools for the Hospital Systems
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    Chapter 7 A Sizing Tool for Allocation Planning of Hospital Bed Resources
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    Chapter 8 A Grid Implementation for Profiling Hospitals Based on Patient Readmissions
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    Chapter 9 A Design for Modelling the Impact of Information and Communication Technologies on Patient Journeys in Neonatal Intensive Care Units
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    Chapter 10 Models for Extracting Information on Patient Pathways
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    Chapter 11 Internal Flows and Frequency of Internal Overflows in a Large Teaching Hospital
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    Chapter 12 Optimal Scheduling Using Length-of-Stay Data for Diverse Routine Procedures
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    Chapter 13 The Impact of Induction Room on Operating Theatre Performances
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    Chapter 14 How Stochasticity and Emergencies Disrupt the Surgical Schedule
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    Chapter 15 Using Markov Systems to Plan Stroke Services
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    Chapter 16 iCOPE: Intelligent Context-Aware Patient Management Systems for Elderly with Cognitive and Functional Impairment
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    Chapter 17 Semantic Smart Homes: Towards Knowledge Rich Assisted Living Environments
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    Chapter 18 Profile Management for Dynamic Groups
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    Chapter 19 Intelligent Patient Management
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Mentioned by

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1 X user

Citations

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8 Dimensions

Readers on

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21 Mendeley
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Title
Intelligent Patient Management
Published by
Springer Science & Business Media, March 2009
DOI 10.1007/978-3-642-00179-6
ISBNs
978-3-64-200178-9, 978-3-64-200179-6
Editors

McClean, Sally, Millard, Peter, El-Darzi, Elia, Nugent, Chris

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 5%
Unknown 20 95%
Readers by discipline Count As %
Computer Science 1 5%
Unknown 20 95%

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