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Information retrieval for pathology information systems

G Miaoulis1, E Protopapa, G Skarpetas

  • 1Technological Educational Institute of Athens, Department of Informatics, Greece.

In Vivo (Athens, Greece)
|July 1, 1993
PubMed
Summary

This study evaluates query formulation techniques like Query-by-Example (QBE), Structured Query Language (SQL), and Graphical Query Language (GCL) for medical information systems. It introduces a novel query processor with a semi-graphical tree structure interface for pathology data summarization.

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Area of Science:

  • Medical Informatics
  • Health Information Systems
  • Database Management

Background:

  • Effective patient data assessment and summarization are crucial in medical information systems.
  • Existing query methods may lack user-friendliness or specific application in pathology.

Purpose of the Study:

  • To evaluate different query formulation techniques for medical information systems.
  • To present a novel query processor for pathology information systems.

Main Methods:

  • Comparative analysis of Query-by-Example (QBE), Structured Query Language (SQL), and Graphical Query Language (GCL).
  • Development and presentation of a query processor featuring a semi-graphical tree structure interface (SGTSI).
  • Integration of summary table handling capabilities within the query processor.

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Main Results:

  • The study evaluates the efficacy of various query formulation techniques.
  • A functional query processor with a unique interface for pathology data is developed.
  • The system supports both complex querying and simple statistical summarization.

Conclusions:

  • The developed query processor enhances data assessment and summarization in pathology information systems.
  • The semi-graphical tree structure interface (SGTSI) offers an intuitive approach to query formulation.
  • This approach addresses the need for versatile patient information handling in healthcare.