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Development and Evaluation of a Case-Based Retrieval Service.

Emilie Pasche1, Marcello Chinali2, Julien Gobeill1

  • 1BiTeM Group, Information Science Department, University of Applied Sciences of Western Switzerland (HES-SO, HEG), Switzerland.

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|April 21, 2017
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Summary
This summary is machine-generated.

This study developed a case-based retrieval (CBR) service for pediatric cardiology cases. The system successfully identified similar patient cases, aiding treatment decisions and improving clinical data management.

Keywords:
Natural language processingelectronic health recordontology

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Area of Science:

  • Medical Informatics
  • Clinical Data Management
  • Artificial Intelligence in Healthcare

Background:

  • Unstructured clinical data poses challenges for effective patient treatment.
  • Case-based retrieval (CBR) systems are crucial for managing large volumes of clinical information.
  • Identifying similar patient cases can inform treatment strategies and predict outcomes.

Purpose of the Study:

  • To develop and evaluate a case-based retrieval (CBR) service for Italian pediatric cardiology cases.
  • To improve the retrieval of similar clinical cases using natural language processing.
  • To assess the precision and effectiveness of the proposed CBR system.

Main Methods:

  • Development of a case-based retrieval (CBR) service utilizing natural language processing.
  • Indexing of pediatric cardiology cases and implementation of a search engine.
  • Incorporation of interactive MeSH normalization and relevance feedback functionalities.
  • Quantitative and qualitative evaluation of the system's performance.

Main Results:

  • The CBR system demonstrated effectiveness in identifying similar patient cases.
  • In over half of the cases, the system suggested a similar episode of care at the first rank.
  • Up to two-thirds of cases received a relevant similar episode suggestion.
  • Qualitative evaluation provided feedback for system improvement.

Conclusions:

  • The developed CBR system shows promise for facilitating clinical decision-making in pediatric cardiology.
  • Relevance feedback strategies can further enhance the precision of the CBR system.
  • The CBR approach is adaptable for multilingual electronic health records (EHR) and other domains.