Limits...
Design of a Global Medical Database which is Searchable by Human Diagnostic Patterns.

Orthuber W, Fiedler G, Kattan M, Sommer T, Fischer-Brandies H - Open Med Inform J (2008)

Bottom Line: Confinement of the result by conventional language based search terms is possible, and immediate individual statistics or regression analyses can quantify probabilities of success in case of different treatment choices.Labeled feature vectors induce a systematic and expandable approach.The database also allows immediate calculation of individual up to date prediction models.

View Article: PubMed Central - PubMed

Affiliation: Department of Orthodontics at University of Kiel, Germany.

ABSTRACT

Unlabelled: We describe a global medical database which is designed for efficient evaluation. It allows language independent search for human diagnostic parameters. Core of the database is a fully automated electronic archive and distribution server for medical histories of real but anonymous patients which contain patterns of diagnosis, chosen treatment, and outcome. Every pattern is represented by a feature vector which is usually a sequence of numbers, and labeled by an unambiguous "pattern name" which identifies its meaning. Similarity search is always done only over patterns with the same pattern name, because these are directly comparable. Similarities of patterns are mapped to spatial similarities (small distances) of their feature vectors using an appropriate metric. This makes them searchable. Pattern names can be "owned" like today domain names. This facilitates unbureaucratic definition of patterns e.g. by manufacturers of diagnostic devices.

Application: If there is a new patient with certain diagnostic patterns, it is possible to combine a part or all of them and to search in the database for completed histories of patients with similar patterns to find the best treatment. Confinement of the result by conventional language based search terms is possible, and immediate individual statistics or regression analyses can quantify probabilities of success in case of different treatment choices.

Conclusions: Efficient searching with diagnostic patterns is technically feasible. Labeled feature vectors induce a systematic and expandable approach. The database also allows immediate calculation of individual up to date prediction models.

No MeSH data available.


Related in: MedlinePlus

The bordered part of Fig. (6c) is stretched that exactly one period remains.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2666959&req=5

F6c: The bordered part of Fig. (6c) is stretched that exactly one period remains.

Mentions: Sometimes complex original data can need complex precalculation. If simple self-evident considerations (Fig. 10) are not enough, an appropriate transformation of pictures, sounds or curves is often the first step for calculation of feature vectors. For example in case of heart sounds a wavelet transformation allows analysis of the signal at different scales and times. Initially it is necessary to select and border accurately a representative period of the sound (Fig. 6a-c). The resulting wavelet coefficients (Fig. 7) can be used for building the feature vector which represents the pattern.


Design of a Global Medical Database which is Searchable by Human Diagnostic Patterns.

Orthuber W, Fiedler G, Kattan M, Sommer T, Fischer-Brandies H - Open Med Inform J (2008)

The bordered part of Fig. (6c) is stretched that exactly one period remains.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2666959&req=5

F6c: The bordered part of Fig. (6c) is stretched that exactly one period remains.
Mentions: Sometimes complex original data can need complex precalculation. If simple self-evident considerations (Fig. 10) are not enough, an appropriate transformation of pictures, sounds or curves is often the first step for calculation of feature vectors. For example in case of heart sounds a wavelet transformation allows analysis of the signal at different scales and times. Initially it is necessary to select and border accurately a representative period of the sound (Fig. 6a-c). The resulting wavelet coefficients (Fig. 7) can be used for building the feature vector which represents the pattern.

Bottom Line: Confinement of the result by conventional language based search terms is possible, and immediate individual statistics or regression analyses can quantify probabilities of success in case of different treatment choices.Labeled feature vectors induce a systematic and expandable approach.The database also allows immediate calculation of individual up to date prediction models.

View Article: PubMed Central - PubMed

Affiliation: Department of Orthodontics at University of Kiel, Germany.

ABSTRACT

Unlabelled: We describe a global medical database which is designed for efficient evaluation. It allows language independent search for human diagnostic parameters. Core of the database is a fully automated electronic archive and distribution server for medical histories of real but anonymous patients which contain patterns of diagnosis, chosen treatment, and outcome. Every pattern is represented by a feature vector which is usually a sequence of numbers, and labeled by an unambiguous "pattern name" which identifies its meaning. Similarity search is always done only over patterns with the same pattern name, because these are directly comparable. Similarities of patterns are mapped to spatial similarities (small distances) of their feature vectors using an appropriate metric. This makes them searchable. Pattern names can be "owned" like today domain names. This facilitates unbureaucratic definition of patterns e.g. by manufacturers of diagnostic devices.

Application: If there is a new patient with certain diagnostic patterns, it is possible to combine a part or all of them and to search in the database for completed histories of patients with similar patterns to find the best treatment. Confinement of the result by conventional language based search terms is possible, and immediate individual statistics or regression analyses can quantify probabilities of success in case of different treatment choices.

Conclusions: Efficient searching with diagnostic patterns is technically feasible. Labeled feature vectors induce a systematic and expandable approach. The database also allows immediate calculation of individual up to date prediction models.

No MeSH data available.


Related in: MedlinePlus