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Related Experiment Videos

Evaluating the web as a clinical knowledge base.

Davis T Bu1, Michael N Cantor

  • 1Partners HealthCare, Boston, MA, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|June 17, 2006
PubMed
Summary

This study developed a novel system using the Google Java API to extract potential medical diagnoses from web searches. The system achieved performance comparable to existing medical expert systems, demonstrating the potential of web data in clinical decision support.

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Medicine

Background:

  • Medical diagnostic decision support systems (MDSS) are crucial in medical informatics.
  • Many existing MDSS were developed before the widespread adoption of the World Wide Web (WWW), limiting their access to current clinical knowledge.
  • The pre-WWW era presented significant constraints on accessing and integrating up-to-date medical information.

Purpose of the Study:

  • To develop a novel system for extracting potential medical diagnoses from general web searches.
  • To leverage the Google Java API for accessing a broader range of clinical knowledge.
  • To evaluate the performance of this new approach against established medical expert systems.

Main Methods:

  • A simple program was created utilizing the Google Java API.

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  • The program was designed to query general web searches for information relevant to potential diagnoses.
  • The system's diagnostic extraction capabilities were assessed and compared to existing expert systems.

    • Main Results:

    • The developed system demonstrated the ability to extract potential diagnoses from general web searches.
    • The system's performance was found to be comparable to that of other established medical expert systems.
    • This indicates the viability of using web search data for diagnostic support.

    Conclusions:

    • Web-based data extraction offers a promising avenue for enhancing medical diagnostic decision support systems.
    • The developed system highlights the potential of integrating readily available online information into clinical informatics tools.
    • Future systems can benefit from leveraging internet resources to overcome knowledge limitations of older systems.