Information Technology in Bio- and Medical Informatics
6th International Conference, ITBAM 2015, Valencia, Spain, September 3-4, 2015, Proceedings
Published on 10. August 2015
X, 115 pages
978-3-319-22741-2 (ISBN)
Description
This book constitutes the refereed proceedings of the 6th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2015, held in Valencia, Spain, in September 2015, in conjunction with DEXA 2015.
The 9 revised long papers presented together with 1 poster paper were carefully reviewed and selected from 15 submissions. The papers address the following two topics: medical terminology and clinical processes and machine learning in biomedicine.
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M. Elena Renda | Miroslav Bursa | Andreas Holzinger
Information Technology in Bio- and Medical Informatics
6th International Conference, ITBAM 2015, Valencia, Spain, September 3-4, 2015, Proceedings
Book
08/2015
Springer
€42.80
Shipment within 10-15 days
Content
- Intro
- Preface
- Organization
- Contents
- Medical Terminology and Clinical Processes
- From Literature to Knowledge: Exploiting PubMed to Answer Biomedical Questions in Natural Language
- 1 Introduction
- 2 Related Work
- 3 Method
- 3.1 Knowledge Base Creation
- 3.2 Data Structure Organization
- 3.3 Question Answering Process
- 4 User Interface for Biomedical Q&A
- 5 Experiments and Validation
- 5.1 Evaluation Metrics
- 5.2 Results
- 6 Conclusions
- References
- Using Twitter Data and Sentiment Analysis to Study Diseases Dynamics
- 1 Introduction
- 2 Architecture
- 2.1 Health-Related Tweets Extraction
- 2.2 Tweets Classification
- 3 Results
- 4 Conclusions
- References
- An Open Data Approach for Clinical Appropriateness
- Abstract
- 1 Introduction
- 2 Background and Related Works
- 3 Our Proposal
- 3.1 Open Data Approach
- 3.2 Appropriateness Rules Management
- 3.3 Architecture Overview
- 4 Experimental Evaluation
- 5 Conclusions
- References
- Machine Learning in Biomedicine
- A Logistic Regression Approach for Identifying Hot Spots in Protein Interfaces
- Abstract
- 1 Introduction
- 2 Material and Method
- 2.1 Benchmark Dataset
- 2.2 Features for Hot Spots Prediction
- 2.2.1 Accessibility
- 2.2.2 Propensity Scaled Sequence Conservation Score
- 2.2.3 Inter-residue Potentials
- 2.2.4 Small-World Structure Characteristics
- 2.2.5 Phi-Psi Interaction Features
- 2.2.6 Contact Number
- 2.3 Logistic Regression Model
- 2.4 Evaluation Measure
- 3 Experiments and Results
- 3.1 Feature Analysis
- 3.2 Comparison with Other Machine Learning Classifiers
- 3.3 Comparison with Existing Prediction Approaches
- 3.4 Case Study
- 4 Conclusion and Future Research
- Acknowledgments
- References
- The Discovery of Prognosis Factors Using Association Rule Mining in Acute Myocardial Infarction with ST-Segment Elevation
- Abstract
- 1 Introduction
- 2 Material and Method
- 2.1 Basic Concepts
- 2.2 Association Rule Mining
- 3 Experiments and Results
- 3.1 Medical Database and Data Coding
- 3.2 Data Cleaning
- 3.3 Risk Factor for Prognosis
- 4 Conclusion and Future Research
- Acknowledgments
- References
- Data Mining Techniques in Health Informatics: A Case Study from Breast Cancer Research
- Abstract
- 1 Introduction
- 2 Background and Related Work
- 2.1 KDD in Health Informatics
- 2.2 Mining Approaches for Breast Cancer Data
- 3 University Hospital Case Study
- 3.1 Clinical Data Environment and EPR
- 3.2 UHS Breast Cancer Data System
- 4 Pre-processing for Data Mining
- 4.1 Research Framework
- 4.2 Breast Cancer Datasets: Data Understanding and Preparation
- 4.3 Disease Event Sequence Profiles
- 5 Experiments and Evaluation
- 5.1 Sequential Patterns Mining
- 5.2 Classification Approaches
- 6 Conclusion
- References
- Artificial Neural Networks in Diagnosis of Liver Diseases
- Abstract
- 1 Introduction
- 2 Knowledge Representation and Reasoning
- 3 A Case Study
- 4 Artificial Neural Networks
- 5 Conclusions and Future Work
- Acknowledgments
- References
- How to Increase the Effectiveness of the Hepatitis Diagnostics by Means of Appropriate Machine Learning Methods
- Abstract
- 1 Introduction
- 1.1 Motivation
- 1.2 Related Work
- 1.3 Methods
- 2 Exploratory Data Analysis
- 3 Predictive Data Mining
- 3.1 HBV Decision Tree for Male Patients with Normal Level of ALT
- 3.2 Optimal Cut-off Points for Selected Attribute
- 4 Conclusion
- Acknowledgment
- References
- Ant-Inspired Algorithms for Decision Tree Induction
- 1 Introduction
- 2 Background Information
- 2.1 Ant Colony Optimization
- 2.2 Decision Trees
- 3 The ACO_DTree Method Description
- 4 Experimental Part
- 4.1 Methodology Overview
- 4.2 Classifiers
- 4.3 Datasets
- 5 Results
- 5.1 Summary
- 6 Conclusion and Discussion
- 6.1 Discussion
- 6.2 Future Work
- References
- Poster Session
- Microsleep Classifier Using EOG Channel Recording: A Feasibility Study
- Abstract
- 1 Introduction
- 2 Methods
- 2.1 Dataset
- 2.2 EOG Signal Feature Extraction
- 3 Results
- 4 Discussions and Conclusions
- Acknowledgment
- References
- Author Index
