Complexity of biomedical data models in cardiology: the Intranet-based AF registry

Dugas, Martin; Hoffmann, Ellen; Janko, Sabine; Hahnewald, Silke; Matis, Tomas; Miller, James R.; Bary, Ch. v.; Farnbacher, A.; Vogler, V.; Überla, K

doi:10.1016/s0169-2607(01)00162-6

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Data Monitoring and Analysis Of A Complex Database2

Introduction1

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Cited by 10 publications

(3 citation statements)

References 16 publications

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“…This tool has been applied to other medical domains 19 and is available on the Internet from http://mdplot.ibe.med.uni-muenchen.de/. Figure 5 provides detailed information on the cytogenetics data (for further information on this kind of analysis see Ref.…”

Section: Data Monitoring and Analysis Of A Complex Databasementioning

confidence: 99%

See 1 more Smart Citation

A comprehensive leukemia database: integration of cytogenetics, molecular genetics and microarray data with clinical information, cytomorphology and immunophenotyping

Dugas¹,

Schoch

Schnittger

et al. 2001

Leukemia

Self Cite

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Section: Data Monitoring and Analysis Of A Complex Databasementioning

confidence: 99%

“…Figure 5 provides detailed information on the cytogenetics data (for further information on this kind of analysis see Ref. 19). …”

Section: Data Monitoring and Analysis Of A Complex Databasementioning

confidence: 99%

A comprehensive leukemia database: integration of cytogenetics, molecular genetics and microarray data with clinical information, cytomorphology and immunophenotyping

Dugas¹,

Schoch

Schnittger

et al. 2001

Leukemia

Self Cite

View full text Add to dashboard Cite

“…In the era of ubiquitous computing, clinical decision support depends on the accessibility to and availability of information at the point of care in a comprehensible format such as clinical reports and patient-specific summaries [20] derived from integrated Electronic Patient Record [21]. Merging and interpretation of data from diverse sources includes integration across multiple dimensions and mapping of models of data collection and processing employed at these sources.…”

Section: Introductionmentioning

confidence: 99%

Anatomy of data integration

Brazhnik

Jones

2007

Journal of Biomedical Informatics

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Producing reliable information is the ultimate goal of data processing. The ocean of data created with the advances of science and technologies calls for integration of data coming from heterogeneous sources that are diverse in their purposes, business rules, underlying models and enabling technologies. Reference models, Semantic Web, standards, ontology, and other technologies enable fast and efficient merging of heterogeneous data, while the reliability of produced information is largely defined by how well the data represent the reality. In this paper, we initiate a framework for assessing the informational value of data that includes data dimensions; aligning data quality with business practices; identifying authoritative sources and integration keys; merging models; uniting updates of varying frequency and overlapping or gapped data sets.

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Supporting Evidence-Based Endocrine Practice

Smith¹,

Gates

Evidence-Based Endocrinology

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Complexity of biomedical data models in cardiology: the Intranet-based AF registry

Cited by 10 publications

References 16 publications

A comprehensive leukemia database: integration of cytogenetics, molecular genetics and microarray data with clinical information, cytomorphology and immunophenotyping

A comprehensive leukemia database: integration of cytogenetics, molecular genetics and microarray data with clinical information, cytomorphology and immunophenotyping

Anatomy of data integration

Supporting Evidence-Based Endocrine Practice

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