Data, Information and Knowledge

Data, Information and Knowledge

Jana Zvárová (Institute of Computer Science of the Academy of Sciences of the Czech Republic and the Center of Biomedical Informatics, Czech Republic) and Arnošt Veselý (Institutes of Computer Science and Information Theory and Automation of the Academy of Sciences of the Czech Republic v.v.i., The Czech Republic)
DOI: 10.4018/978-1-60566-218-3.ch001
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This chapter introduces the basic concepts of medical informatics: data, information, and knowledge. Data are classified into various types and illustrated by concrete medical examples. The concept of knowledge is formalized in the framework of a language related to objects, properties, and relations within ontology. Various aspects of knowledge are studied and illustrated on examples dealing with symptoms and diseases. Several approaches to the concept of information are systematically studied, namely the Shannon information, the discrimination information, and the decision information. Moreover, information content of theoretical knowledge is introduced. All these approaches to information are illustrated on one simple medical example.
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Healthcare is an information-intensive sector. The need to develop and organize new ways of providing health information, data and knowledge has been accompanied by major advances in information and communication technologies. These new technologies are speeding an exchange and use of data, information and knowledge and are eliminating geographical and time barriers. These processes highly accelerated medical informatics development. Opinion that medical informatics is just a computer application in healthcare, an applied discipline that has not acquired its own theory is slowly disappearing. Nowadays medical informatics shows its significance as a multidisciplinary science developed on the basis of interaction of information sciences with medicine and health care in accordance with the attained level of information technology. Today’s healthcare environments use electronic health records that are shared between computer systems and which may be distributed over many locations and between organizations, in order to provide information to internal users, to payers and to respond to external requests. With increasing mobility of populations, patient data is accumulating in different places, but it needs to be accessible in an organized manner on a national and even global scale. Large amounts of information may be accessed via remote workstations and complex networks supporting one or more organizations, and potentially this may happen within a national information infrastructure.

Medical informatics now exists more then 40 years and it has been rapidly growing in the last decade. Despite of major advantages in the science and technology of health care it seems that medical informatics discipline has the potential to improve and facilitate the ever-changing and ever-broadening mass of information concerning the etiology, prevention and treatment of diseases as well as the maintenance of health. Its very broad field of interest is covering many multidisciplinary research topics with consequences for patient care and education. There have been different views on informatics. One definition of informatics declares informatics as the discipline that deals with information (Gremy, 1989). However, there are also other approaches. We should remind that the term of informatics was adopted in the sixties in some European countries (e.g. Germany and France) to denote what in other countries (e.g. in USA) was known as computer science (Moehr, 1989). In the sixties the term informatics was also used in Russia for the discipline concerned with bibliographic information processing (Russian origins of this concept are also mentioned in (Colens, 1986)). These different views on informatics led to different views on medical informatics. In 1997 the paper (Haux, 1997) initiated the broad discussion on the medical informatics discipline. The paper (Zvárová, 1997) the view on medical informatics structure is based on the structuring of informatics into four information rings and their intersections with the field of medicine, comprising also healthcare. These information rings are displayed on Figure 1.

Figure 1.

Structure of informatics

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Editorial Advisory Board
Table of Contents
Riccardo Bellazzi
Petr Berka, Jan Rauch, Djamel Abdelkader Zighed
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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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