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Analysis of information in indicant-patterns

A L Laursen, I S Thomsen, S B Larsen

    Acta Psychiatrica Scandinavica
    |October 1, 1981
    PubMed
    Summary
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    This study introduces a method to select optimal data patterns for consistent evaluation across different criteria. It ensures pattern validity for diagnostics and treatment choices using Bayesian methods.

    Area of Science:

    • Decision analysis
    • Medical informatics
    • Pattern recognition

    Background:

    • Diagnostic conclusions can be reached through various information patterns.
    • The validity of these patterns for criteria beyond diagnosis, such as treatment selection, is not well understood.

    Purpose of the Study:

    • To describe a procedure for selecting optimal data patterns.
    • To analyze the validity of these patterns across different criteria.
    • To ensure consistent evaluation of permissible patterns/syndromes.

    Main Methods:

    • Utilizes Bayes' methodology for pattern selection and validity analysis.
    • Incorporates continuous correction for redundancy between indicants.
    • Formulates and evaluates permissible patterns/syndromes consistently.

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    Main Results:

    • A procedure for selecting optimal data patterns and analyzing their validity is presented.
    • The method allows for consistent evaluation of patterns across diverse criteria.
    • Addresses the uncertainty regarding pattern validity for non-diagnostic outcomes.

    Conclusions:

    • The described procedure provides a robust framework for selecting and validating data patterns.
    • Ensures that chosen data patterns are reliable for multiple decision-making criteria.
    • Offers a consistent approach to evaluating diagnostic and treatment-related information patterns.