Developing multilevel search filters for clinical questions represented as conceptual graphs

Area of Science:

• Information Science
• Medical Informatics

Background:

• Effective retrieval of clinical documents is crucial for evidence-based practice.
• Existing search methods may lack precision, leading to information overload.

Purpose of the Study:

• To develop and implement a search strategy model for high-precision document retrieval in response to clinical queries.
• To optimize the process of finding relevant medical literature.

Main Methods:

• Designed a staged configuration of search filters.
• Implemented a model that retrieves documents from most precise to least specific.
• Tested the model's effectiveness in a simulated clinical query environment.

Main Results:

• The search strategy model successfully retrieved relevant documents with high precision.
• Most pertinent articles were identified at the initial stages of the search process.
• The staged filtering approach proved effective for various clinical queries.

Conclusions:

• The proposed search strategy model enhances the efficiency and precision of clinical document retrieval.
• Early-stage retrieval of relevant articles is achievable with the implemented model.
• This approach can significantly aid healthcare professionals in accessing timely and accurate information.