Literature DB >> 23916863

eTACTS: a method for dynamically filtering clinical trial search results.

Riccardo Miotto1, Silis Jiang, Chunhua Weng.   

Abstract

OBJECTIVE: Information overload is a significant problem facing online clinical trial searchers. We present eTACTS, a novel interactive retrieval framework using common eligibility tags to dynamically filter clinical trial search results.
MATERIALS AND METHODS: eTACTS mines frequent eligibility tags from free-text clinical trial eligibility criteria and uses these tags for trial indexing. After an initial search, eTACTS presents to the user a tag cloud representing the current results. When the user selects a tag, eTACTS retains only those trials containing that tag in their eligibility criteria and generates a new cloud based on tag frequency and co-occurrences in the remaining trials. The user can then select a new tag or unselect a previous tag. The process iterates until a manageable number of trials is returned. We evaluated eTACTS in terms of filtering efficiency, diversity of the search results, and user eligibility to the filtered trials using both qualitative and quantitative methods.
RESULTS: eTACTS (1) rapidly reduced search results from over a thousand trials to ten; (2) highlighted trials that are generally not top-ranked by conventional search engines; and (3) retrieved a greater number of suitable trials than existing search engines. DISCUSSION: eTACTS enables intuitive clinical trial searches by indexing eligibility criteria with effective tags. User evaluation was limited to one case study and a small group of evaluators due to the long duration of the experiment. Although a larger-scale evaluation could be conducted, this feasibility study demonstrated significant advantages of eTACTS over existing clinical trial search engines.
CONCLUSION: A dynamic eligibility tag cloud can potentially enhance state-of-the-art clinical trial search engines by allowing intuitive and efficient filtering of the search result space.
Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Association rules; Clinical trials; Dynamic information filtering; Information storage and retrieval; Interactive information retrieval; Tag cloud

Mesh:

Year:  2013        PMID: 23916863      PMCID: PMC3843999          DOI: 10.1016/j.jbi.2013.07.014

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  26 in total

1.  Generating medical logic modules for clinical trial eligibility criteria.

Authors:  Craig G Parker; David W Embley
Journal:  AMIA Annu Symp Proc       Date:  2003

2.  A practical method for transforming free-text eligibility criteria into computable criteria.

Authors:  Samson W Tu; Mor Peleg; Simona Carini; Michael Bobak; Jessica Ross; Daniel Rubin; Ida Sim
Journal:  J Biomed Inform       Date:  2010-09-17       Impact factor: 6.317

3.  An interface-driven analysis of user interactions with an electronic health records system.

Authors:  Kai Zheng; Rema Padman; Michael P Johnson; Herbert S Diamond
Journal:  J Am Med Inform Assoc       Date:  2008-12-11       Impact factor: 4.497

4.  Automated information extraction of key trial design elements from clinical trial publications.

Authors:  Berry de Bruijn; Simona Carini; Svetlana Kiritchenko; Joel Martin; Ida Sim
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

5.  Unsupervised mining of frequent tags for clinical eligibility text indexing.

Authors:  Riccardo Miotto; Chunhua Weng
Journal:  J Biomed Inform       Date:  2013-09-10       Impact factor: 6.317

6.  A human-computer collaborative approach to identifying common data elements in clinical trial eligibility criteria.

Authors:  Zhihui Luo; Riccardo Miotto; Chunhua Weng
Journal:  J Biomed Inform       Date:  2012-07-27       Impact factor: 6.317

7.  The Unified Medical Language System.

Authors:  D A Lindberg; B L Humphreys; A T McCray
Journal:  Methods Inf Med       Date:  1993-08       Impact factor: 2.176

8.  Assessing the impact of user-centered research on a clinical trial eHealth tool via counterbalanced research design.

Authors:  Nancy L Atkinson; Holly A Massett; Christy Mylks; Lauren A McCormack; Julia Kish-Doto; Bradford W Hesse; Min Qi Wang
Journal:  J Am Med Inform Assoc       Date:  2011 Jan-Feb       Impact factor: 4.497

9.  Analysis of eligibility criteria complexity in clinical trials.

Authors:  Jessica Ross; Samson Tu; Simona Carini; Ida Sim
Journal:  Summit Transl Bioinform       Date:  2010-03-01

10.  An Internet-based cancer clinical trials matching resource.

Authors:  James M Metz; Carolyn Coyle; Courtney Hudson; Margaret Hampshire
Journal:  J Med Internet Res       Date:  2005-07-01       Impact factor: 5.428

View more
  12 in total

1.  A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records.

Authors:  C Weng; Y Li; P Ryan; Y Zhang; F Liu; J Gao; J T Bigger; G Hripcsak
Journal:  Appl Clin Inform       Date:  2014-05-07       Impact factor: 2.342

2.  Adaptive semantic tag mining from heterogeneous clinical research texts.

Authors:  T Hao; C Weng
Journal:  Methods Inf Med       Date:  2014-10-20       Impact factor: 2.176

3.  Visual aggregate analysis of eligibility features of clinical trials.

Authors:  Zhe He; Simona Carini; Ida Sim; Chunhua Weng
Journal:  J Biomed Inform       Date:  2015-01-20       Impact factor: 6.317

4.  Clustering clinical trials with similar eligibility criteria features.

Authors:  Tianyong Hao; Alexander Rusanov; Mary Regina Boland; Chunhua Weng
Journal:  J Biomed Inform       Date:  2014-02-01       Impact factor: 6.317

5.  Valx: A System for Extracting and Structuring Numeric Lab Test Comparison Statements from Text.

Authors:  Tianyong Hao; Hongfang Liu; Chunhua Weng
Journal:  Methods Inf Med       Date:  2016-03-04       Impact factor: 2.176

6.  Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials.

Authors:  Riccardo Miotto; Chunhua Weng
Journal:  J Am Med Inform Assoc       Date:  2015-03-13       Impact factor: 4.497

7.  Cross-system evaluation of clinical trial search engines.

Authors:  Silis Y Jiang; Chunhua Weng
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2014-04-07

8.  Automatic classification of registered clinical trials towards the Global Burden of Diseases taxonomy of diseases and injuries.

Authors:  Ignacio Atal; Jean-David Zeitoun; Aurélie Névéol; Philippe Ravaud; Raphaël Porcher; Ludovic Trinquart
Journal:  BMC Bioinformatics       Date:  2016-09-22       Impact factor: 3.169

9.  A Semantic Web-based System for Mining Genetic Mutations in Cancer Clinical Trials.

Authors:  Sambhawa Priya; Guoqian Jiang; Surendra Dasari; Michael T Zimmermann; Chen Wang; Jeff Heflin; Christopher G Chute
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2015-03-25

10.  Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining.

Authors:  S Sadesh; R C Suganthe
Journal:  ScientificWorldJournal       Date:  2015-06-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.