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Using schemas for diagnosis.

R M Turner1

  • 1School of Information and Computer Science, Georgia Institute of Technology, Atlanta 30332.

Computer Methods and Programs in Biomedicine
|October 1, 1989
PubMed
Summary
This summary is machine-generated.

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This study introduces schema-based reasoning for medical diagnosis, enabling dynamic plan adjustments. The MEDIC system demonstrates this approach in pulmonology, integrating planning and execution for evolving patient information.

Area of Science:

  • Artificial Intelligence
  • Medical Informatics
  • Clinical Decision Support

Background:

  • Medical diagnosis is complex, involving dynamic planning and execution.
  • Traditional planning struggles with emergent information during diagnosis.
  • The need for adaptive reasoning in medical decision-making is critical.

Purpose of the Study:

  • To introduce schema-based reasoning as a novel approach for medical diagnosis.
  • To develop a system capable of interleaving planning and execution in diagnostic tasks.
  • To address the challenge of dynamic information in medical decision-making.

Main Methods:

  • Procedural knowledge is represented as schemas.
  • Schemas are retrieved and applied based on diagnostic goals and patient data.

Related Experiment Videos

  • Reasoning involves selecting active schemas using situational and strategic information.

    • Main Results:

    • Schema-based reasoning allows for dynamic plan adaptation.
    • The MEDIC system, implementing this approach, functions within the pulmonology domain.
    • The system effectively interleaves planning and execution for diagnostic reasoning.

    Conclusions:

    • Schema-based reasoning offers a robust framework for medical diagnosis.
    • The MEDIC system provides a practical implementation of adaptive diagnostic reasoning.
    • This approach enhances the ability of diagnostic systems to handle evolving patient information.