Atigeo at TREC 2014 Clinical Decision Support Task

Abstract

The TREC 2014 Clinical Decision Support Track task involves retrieval and ranking of medical journal articles with respect to their relevance to prescribing tests, diagnosing or treating a patient represented in a short case report. The Atigeo xPatterns platform supports a variety of ensemble methods for developing and tuning information retrieval (IR) system components for a task and/or domain using labeled data. For TREC 2014, we combine results from an ensemble of search engines, each with a configurable suite of natural language processing (NLP) components, to compute a relevance score for each article and topic. We describe our ensemble approach, the strategies and tools we use to create labeled data to support this approach, the components in our IR / NLP pipeline, and our results on the TREC 2014 CDS task.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2014
Accession Number
ADA618775

Entities

People

  • Alex Thomas
  • Chenchieh Hsu
  • Joseph F. Mccarthy
  • Yishul Wei

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Age Groups
  • Birth
  • Computational Linguistics
  • Control Systems
  • Databases
  • Information Retrieval
  • Language
  • Linguistics
  • Magnetic Resonance
  • Natural Language Processing
  • Pipelines
  • Preprocessing
  • Respiration
  • Respiration Disorders
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Information Retrieval
  • Neural Network Machine Learning.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval