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Clinical Information Retrieval: A Literature Review.

Sonish Sivarajkumar1, Haneef Ahamed Mohammad2, David Oniani3

  • 1Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA USA.

Journal of Healthcare Informatics Research
|April 29, 2024
PubMed
Summary

This scoping review examines clinical information retrieval (IR) research, identifying gaps in methods like indexing and ranking. It highlights the need for advanced systems, including neural IR and semantic vector search, for better medical data access.

Keywords:
ApplicationsElectronic health recordsInformation retrievalNatural language processingTools

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Area of Science:

  • Medical Informatics
  • Information Science
  • Computer Science

Background:

  • Clinical information retrieval (IR) is crucial for accessing and analyzing medical literature.
  • Efficient IR supports clinicians and researchers in healthcare.
  • Current research needs a comprehensive overview to identify future directions.

Purpose of the Study:

  • To provide a comprehensive overview of clinical IR research.
  • To identify research gaps and opportunities in clinical IR.
  • To analyze methods, techniques, and tools for medical information retrieval.

Main Methods:

  • Scoping review adhering to PRISMA guidelines.
  • Extensive literature search across multiple databases (Embase, Medline, Scopus, ACM, IEEE, Web of Science).
  • Inclusion of 184 papers published between January 1, 2010, and January 4, 2023.

Main Results:

  • Detailed analysis of clinical IR landscape: publication trends, data sources, methodologies, evaluation metrics, and applications.
  • Identified key research gaps in clinical IR methods: indexing, ranking, and query expansion.
  • Highlighted the need for advanced clinical IR systems, including semantic vector search and neural IR techniques.

Conclusions:

  • The review serves as a framework for future clinical IR research.
  • There is an imperative for innovative research in clinical IR methods.
  • Advanced techniques are needed for effective retrieval from unstructured electronic health records (EHRs).