Mining Tinnitus Database for Knowledge

Mining Tinnitus Database for Knowledge

Pamela L. Thompson (University of North Carolina at Charlotte, USA), Xin Zhang (University of North Carolina at Pembroke, USA), Wenxin Jiang (University of North Carolina at Charlotte, USA), Zbigniew W. Ras (University of North Carolina at Charlotte, USA) and Pawel Jastreboff (Emory University School of Medicine, USA)
DOI: 10.4018/978-1-60566-218-3.ch014
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Abstract

This chapter describes the process used to mine a database containing data, related to patient visits during Tinnitus Retraining Therapy. The original collection of datasets containing diagnostic and treatment data on tinnitus patients and visits was collected by P. Jastreboff. This sparse dataset consisted of eleven tables primarily related by patient id, number, and date of visit. First, with the help of P. Jastreboff, we gained an understanding of the domain knowledge spanning different disciplines (including otology and audiology), and then we used this knowledge to extract, transform, and mine the constructed database. Complexities were encountered with temporal data and text mining of certain features.The researchers focused on analysis of existing data, along with automating the discovery of new and useful features in order to improve classification and understanding of tinnitus diagnosis.
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Domain Knowledge

The domain knowledge for tinnitus involves many disciplines, primarily including otology and audiology. Tinnitus appears to be caused by a variety of factors including exposure to loud noises, head trauma, and a variety of diseases. An interesting fact is that tinnitus can be induced in 94% of the population by a few minutes of sound deprivation (Heller & Bergman, 1953).

Decreased sound tolerance frequently accompanies tinnitus and can include symptoms of hyperacucisis (an abnormal enhancement of signal within the auditory pathways), misophonia (a strong dislike of sound) or phonophobia (a fear of sound) (Jastreboff, 2004). Past approaches to treatment tend to have been based on anecdotal observations and treatment often focused on tinnitus suppression. Currently a wide variety of approaches are utilized, ranging from sound use to drugs or electrical or magnetical stimulation of the auditory cortex.

Jastreboff (1995) offers an important new model (hence treatment) for tinnitus that focuses on the phantom aspects of tinnitus with tinnitus resulting exclusively from activity within the nervous system that is not related to corresponding activity with the cochlea or external stimulation. The model furthermore stresses that in cases of clinically-significant tinnitus, various structures in the brain, particularly the limbic and autonomic nervous system, prefrontal cortex, and reticular formations play a dominant role with the auditory system being secondary.

Tinnitus Retraining Therapy (TRT), developed by Jastreboff, is a treatment model with a high rate of success (over 80% of the cases) and is based on the neurophysical model of tinnitus. Neurophysiology is a branch of science focusing on the physiological aspect of nervous system function (Jastreboff, 2004). Tinnitus Retraining Therapy “cures” tinnitus-evoked reactions by retraining its association with specific centers throughout the nervous system, particularly the limbic and autonomic systems.

The limbic nervous system (emotions) controls fear, thirst, hunger, joy and happiness and is involved in learning, memory, and stress. The limbic nervous system is connected with all sensory systems. The autonomic nervous system controls functions of the brain and the body over which we have limited control, e.g., heart beating, blood pressure, and release of hormones. The limbic and autonomic nervous systems are involved in stress, annoyance, anxiety etc. When these systems become activated by tinnitus-related neuronal activity (tinnitus signal) negative symptoms are evoked (Jastreboff, 2004). Unfortunately, many patients seeking treatment other than TRT are often told that nothing can be done about their tinnitus. This can have the negative effect of enhancing the limbic nervous system reactions, which then can cause strengthening of the negative effect of the tinnitus on a patient (see Figure 1: Block diagram of the neurophysiological model of tinnitus (Jastreboff, 2004)).

Figure 1.

Block diagram of the neurophysiological model of tinnitus

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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