Mining Tuberculosis Data

Mining Tuberculosis Data

Marisa A. Sánchez (Universidad Nacional del Sur, Argentina), Sonia Uremovich (Universidad Nacional del Sur, Argentina) and Pablo Acrogliano (Hospital Interzonal Dr. José Penna, Argentina)
DOI: 10.4018/978-1-60566-218-3.ch016
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Abstract

This chapter reviews the current policies of tuberculosis control programs for the diagnosis of tuberculosis. The international standard for tuberculosis control is the World Health Organization’s DOT (Direct Observation of Therapy) strategy that aims to reduce the transmission of the infection through prompt diagnosis and effective treatment of symptomatic tuberculosis patients who present at health care facilities. Physicians are concerned about the poor specificity of diagnostic methods and the increase in the notification of relapse cases. This works describes a data-mining project that uses DOT´s data to analyze the relationship among different variables and the tuberculosis diagnostic category registered for each patient.
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Background

Technology evolution has promoted the increase in the volume and variety of data. The amount of data increases exponentially with time. As a consequence, the manual analysis of this data is complex and prone to errors. When the amount of data to be analyzed exploded in the mid-1990s, knowledge discovery emerged as an important analytical tool. The process of extracting useful knowledge from volumes of data is known as knowledge discovery in databases (Fayyad, 1996). Knowledge discovery’s major objective is to identify valid, novel, potentially useful, and understandable patterns of data. Knowledge discovery is supported by three technologies: massive data collection, powerful multiprocessor computers, and data mining (Turban, 2005).

Data mining derives its name from the similarities between searching for valuable business information in a large database, and mining a mountain for a vein of valuable ore. Data mining can generate new business opportunities by providing automated prediction of trends and behaviors, and discovery of previously unknown patterns.

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Table of Contents
Foreword
Riccardo Bellazzi
Preface
Petr Berka, Jan Rauch, Djamel Abdelkader Zighed
Acknowledgment
Petr Berka, Jan Rauch, Djamel Abdelkader Zighed
Chapter 1
Jana Zvárová, Arnošt Veselý
This chapter introduces the basic concepts of medical informatics: data, information, and knowledge. Data are classified into various types and... Sample PDF
Data, Information and Knowledge
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Chapter 2
Michel Simonet, Radja Messai, Gayo Diallo
Health data and knowledge had been structured through medical classifications and taxonomies long before ontologies had acquired their pivot status... Sample PDF
Ontologies in the Health Field
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Chapter 3
Alberto Freitas, Pavel Brazdil, Altamiro Costa-Pereira
This chapter introduces cost-sensitive learning and its importance in medicine. Health managers and clinicians often need models that try to... Sample PDF
Cost-Sensitive Learning in Medicine
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Chapter 4
Arnošt Veselý
This chapter deals with applications of artificial neural networks in classification and regression problems. Based on theoretical analysis it... Sample PDF
Classification and Prediction with Neural Networks
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Chapter 5
Patrik Eklund, Lena Kallin Westin
Classification networks, consisting of preprocessing layers combined with well-known classification networks, are well suited for medical data... Sample PDF
Preprocessing Perceptrons and Multivariate Decision Limits
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Chapter 6
Xiu Ying Wang, Dagan Feng
The rapid advance and innovation in medical imaging techniques offer significant improvement in healthcare services, as well as provide new... Sample PDF
Image Registration for Biomedical Information Integration
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Chapter 7
ECG Processing  (pages 137-160)
Lenka Lhotská, Václav Chudácek, Michal Huptych
This chapter describes methods for preprocessing, analysis, feature extraction, visualization, and classification of electrocardiogram (ECG)... Sample PDF
ECG Processing
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Chapter 8
EEG Data Mining Using PCA  (pages 161-180)
Lenka Lhotská, Vladimír Krajca, Jitka Mohylová, Svojmil Petránek, Václav Gerla
This chapter deals with the application of principal components analysis (PCA) to the field of data mining in electroencephalogram (EEG) processing.... Sample PDF
EEG Data Mining Using PCA
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Chapter 9
Darryl N. Davis, Thuy T.T. Nguyen
Risk prediction models are of great interest to clinicians. They offer an explicit and repeatable means to aide the selection, from a general... Sample PDF
Generating and Verifying Risk Prediction Models using Data Mining
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Chapter 10
Vangelis Karkaletsis, Konstantinos Stamatakis, Karampiperis, Karampiperis, Pythagoras Karampiperis, Pythagoras Karampiperis
The World Wide Web is an important channel of information exchange in many domains, including the medical one. The ever increasing amount of freely... Sample PDF
Management of Medical Website Quality Labels via Web Mining
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Chapter 11
Rainer Schmidt
In medicine, a lot of exceptions usually occur. In medical practice and in knowledge-based systems, it is necessary to consider them and to deal... Sample PDF
Two Case-Based Systems for Explaining Exceptions in Medicine
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Chapter 12
Bruno Crémilleux, Arnaud Soulet, Jiri Kléma, Céline Hébert, Olivier Gandrillon
The discovery of biologically interpretable knowledge from gene expression data is a crucial issue. Current gene data analysis is often based on... Sample PDF
Discovering Knowledge from Local Patterns in SAGE Data
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Chapter 13
Jirí Kléma, Filip Železný, Igor Trajkovski, Filip Karel, Bruno Crémilleux
This chapter points out the role of genomic background knowledge in gene expression data mining. The authors demonstrate its application in several... Sample PDF
Gene Expression Mining Guided by Background Knowledge
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Chapter 14
Pamela L. Thompson, Xin Zhang, Wenxin Jiang, Zbigniew W. Ras, Pawel Jastreboff
This chapter describes the process used to mine a database containing data, related to patient visits during Tinnitus Retraining Therapy. The... Sample PDF
Mining Tinnitus Database for Knowledge
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Chapter 15
Dinora A. Morales, Endika Bengoetxea, Pedro Larrañaga
Infertility is currently considered an important social problem that has been subject to special interest by medical doctors and biologists. Due to... Sample PDF
Gaussian-Stacking Multiclassifiers for Human Embryo Selection
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Chapter 16
Mining Tuberculosis Data  (pages 332-349)
Marisa A. Sánchez, Sonia Uremovich, Pablo Acrogliano
This chapter reviews the current policies of tuberculosis control programs for the diagnosis of tuberculosis. The international standard for... Sample PDF
Mining Tuberculosis Data
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Chapter 17
Mila Kwiatkowska, M. Stella Atkins, Les Matthews, Najib T. Ayas, C. Frank Ryan
This chapter describes how to integrate medical knowledge with purely inductive (data-driven) methods for the creation of clinical prediction rules.... Sample PDF
Knowledge-Based Induction of Clinical Prediction Rules
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Chapter 18
Petr Berka, Jan Rauch, Marie Tomecková
The aim of this chapter is to describe goals, current results, and further plans of long-time activity concerning application of data mining and... Sample PDF
Data Mining in Atherosclerosis Risk Factor Data
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About the Contributors