Related Experiment Video
Updated: May 5, 2026
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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
9.6K
Towards dynamic and interactive retrieval of clinical trials using common eligibility features
Riccardo Miotto1, Chunhua Weng
1Department of Biomedical Informatics, Columbia University, New York, NY.
Summary
Finding clinical trials online is challenging due to information overload. Our framework dynamically refines search results using extracted features, reducing thousands of options to a manageable number for patients.
Area of Science:
- Health Informatics
- Clinical Trial Recruitment
Background:
- Patients face significant information overload when searching for clinical trials online.
- Existing search methods often yield an unmanageable number of results, hindering patient participation.
Purpose of the Study:
- To develop a framework for dynamically refining clinical trial search results.
- To reduce the number of search results to a manually reviewable quantity.
Main Methods:
- Extracted frequent features from eligibility criteria of a subset of clinical trials offline.
- Presented features dynamically to users based on co-occurrences and interactions.
- Tested the framework on ClinicalTrials.gov data.
Main Results:
- A simple search yielding over a thousand results was reduced to ten.
- Achieved significant reduction using an average of four extracted features.
Conclusions:
- The proposed framework effectively addresses information overload in clinical trial searches.
- Dynamic feature refinement offers a practical solution for improving patient access to relevant clinical trials.
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