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Advances in Artificial Intelligence - IBERAMIA 2016

Overview of attention for book
Advances in Artificial Intelligence - IBERAMIA 2016
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 1 Towards an Integration of Workflows and Clinical Guidelines: A Case Study
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    Chapter 2 Anomalies Detection in the Behavior of Processes Using the Sensor Validation Theory
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    Chapter 3 Explanatory Relations Revisited: Links with Credibility-Limited Revision
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    Chapter 4 Semantic Enrichment of Web Service Operations
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    Chapter 5 The ICARO Goal Driven Agent Pattern
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    Chapter 6 A Study for Self-adapting Urban Traffic Control
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    Chapter 7 A Constraint-Based Approach for the Conciliation of Clinical Guidelines
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    Chapter 8 Intelligence Amplification Framework for Enhancing Scheduling Processes
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    Chapter 9 A Column Generation Approach for Solving a Green Bi-objective Inventory Routing Problem
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    Chapter 10 Enhancing Semi-supevised Text Classification Using Document Summaries
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    Chapter 11 A Comparison Between Two Spanish Sentiment Lexicons in the Twitter Sentiment Analysis Task
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    Chapter 12 Is This a Joke? Detecting Humor in Spanish Tweets
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    Chapter 13 Evaluating Topic-Based Representations for Author Profiling in Social Media
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    Chapter 14 Using Robustness to Learn to Order Semantic Properties in Referring Expression Generation
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    Chapter 15 Conditional Random Fields for Spanish Named Entity Recognition Using Unsupervised Features
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    Chapter 16 Detection of Fraud Symptoms in the Retail Industry
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    Chapter 17 A Machine Learning Model for Occupancy Rates and Demand Forecasting in the Hospitality Industry
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    Chapter 18 A Machine Learning Model for Triage in Lean Pediatric Emergency Departments
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    Chapter 19 An Empirical Validation of Learning Schemes Using an Automated Genetic Defect Prediction Framework
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    Chapter 20 Machine Learning Approaches to Estimate Simulated Cardiac Ejection Fraction from Electrical Impedance Tomography
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    Chapter 21 Machine Learning Models for Early Dengue Severity Prediction
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    Chapter 22 Early Prediction of Severe Maternal Morbidity Using Machine Learning Techniques
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    Chapter 23 Collaborative Filtering with Semantic Neighbour Discovery
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    Chapter 24 Distributed and Parallel Algorithm for Computing Betweenness Centrality
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    Chapter 25 Principal Curves and Surfaces to Interval Valued Variables
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    Chapter 26 In Defense of Online Kmeans for Prototype Generation and Instance Reduction
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    Chapter 27 In Search of Truth: Analysis of Smile Intensity Dynamics to Detect Deception
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    Chapter 28 Sign Languague Recognition Without Frame-Sequencing Constraints: A Proof of Concept on the Argentinian Sign Language
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    Chapter 29 Automatic Generation of Type-1 and Interval Type-2 Membership Functions for Prediction of Time Series Data
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    Chapter 30 Calibration of Microscopic Traffic Flow Simulation Models Using a Memetic Algorithm with Solis and Wets Local Search Chaining (MA-SW-Chains)
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    Chapter 31 A New Strategy Based on Feature Selection for Fault Classification in Transmission Lines
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    Chapter 32 Context Ontologies in Ubiquitous Learning Environments
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    Chapter 33 An Interactive Tool to Support Student Assessment in Programming Assignments
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    Chapter 34 Hidden Markov Models for Artificial Voice Production and Accent Modification
Attention for Chapter 22: Early Prediction of Severe Maternal Morbidity Using Machine Learning Techniques
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Citations

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Chapter title
Early Prediction of Severe Maternal Morbidity Using Machine Learning Techniques
Chapter number 22
Book title
Advances in Artificial Intelligence - IBERAMIA 2016
Published by
Springer International Publishing, January 2016
DOI 10.1007/978-3-319-47955-2_22
Book ISBNs
978-3-31-947954-5, 978-3-31-947955-2
Authors

Eugenia Arrieta Rodríguez, Francisco Edna Estrada, William Caicedo Torres, Juan Carlos Martínez Santos

Editors

Manuel Montes y Gómez, Hugo Jair Escalante, Alberto Segura, Juan de Dios Murillo

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 18%
Student > Bachelor 5 13%
Student > Master 5 13%
Lecturer 3 8%
Professor 2 5%
Other 4 11%
Unknown 12 32%
Readers by discipline Count As %
Computer Science 11 29%
Engineering 4 11%
Medicine and Dentistry 4 11%
Nursing and Health Professions 3 8%
Mathematics 1 3%
Other 1 3%
Unknown 14 37%

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