WaterlooClarke: TREC 2015 Clinical Decision Support Track

Abstract

Clinical decision support systems help physicians with finding additional information about a particular medical case. In this paper, we develop a clinical decision support system that, based on a short medical case description, can recommend research articles to answer some common medical questions (diagnosis, test and treatment articles). The two different full-text search engines we adopted in order to search over the collection of articles are Terrier and Apache Solr. We test each search engine with different settings and retrieval algorithms. Additionally, we combine the results of the two different search engines using reciprocal rank fusion. The evaluation of the submitted runs using partially marked results of Text Retrieval Conference (TREC) from the previous year shows that the methodologies are promising.

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 2015
Accession Number
AD1004863

Entities

People

  • Amira Ghenai
  • Charles L. Clarke
  • Eldar Khalilov
  • Pavel Valov

Organizations

  • University of Waterloo

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Algorithms
  • Biomedical Research
  • Body Weight
  • Computer Science
  • Computers
  • Databases
  • Decision Support Systems
  • Feedback
  • Filtration
  • Information Retrieval
  • Knowledge Management
  • Pain
  • Physicians
  • Respiration Disorders
  • Stemming

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Clinical Trial Research.
  • Information Retrieval