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An interactive retrieval system for clinical trial studies with context-dependent protocol elements
A well-defined protocol for a clinical trial guarantees a successful outcome report. When designing the protocol, most researchers refer to electronic databases and extract protocol elements using a keyword search. However, state-of-the-art database systems only offer text-based searches for user-en...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500653/ https://www.ncbi.nlm.nih.gov/pubmed/32946464 http://dx.doi.org/10.1371/journal.pone.0238290 |
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author | Park, Junseok Park, Seongkuk Kim, Kwangmin Hwang, Woochang Yoo, Sunyong Yi, Gwan-su Lee, Doheon |
author_facet | Park, Junseok Park, Seongkuk Kim, Kwangmin Hwang, Woochang Yoo, Sunyong Yi, Gwan-su Lee, Doheon |
author_sort | Park, Junseok |
collection | PubMed |
description | A well-defined protocol for a clinical trial guarantees a successful outcome report. When designing the protocol, most researchers refer to electronic databases and extract protocol elements using a keyword search. However, state-of-the-art database systems only offer text-based searches for user-entered keywords. In this study, we present a database system with a context-dependent and protocol-element-selection function for successfully designing a clinical trial protocol. To do this, we first introduce a database for a protocol retrieval system constructed from individual protocol data extracted from 184,634 clinical trials and 13,210 frame structures of clinical trial protocols. The database contains a variety of semantic information that allows the filtering of protocols during the search operation. Based on the database, we developed a web application called the clinical trial protocol database system (CLIPS; available at https://corus.kaist.edu/clips). This system enables an interactive search by utilizing protocol elements. To enable an interactive search for combinations of protocol elements, CLIPS provides optional next element selection according to the previous element in the form of a connected tree. The validation results show that our method achieves better performance than that of existing databases in predicting phenotypic features. |
format | Online Article Text |
id | pubmed-7500653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75006532020-09-24 An interactive retrieval system for clinical trial studies with context-dependent protocol elements Park, Junseok Park, Seongkuk Kim, Kwangmin Hwang, Woochang Yoo, Sunyong Yi, Gwan-su Lee, Doheon PLoS One Research Article A well-defined protocol for a clinical trial guarantees a successful outcome report. When designing the protocol, most researchers refer to electronic databases and extract protocol elements using a keyword search. However, state-of-the-art database systems only offer text-based searches for user-entered keywords. In this study, we present a database system with a context-dependent and protocol-element-selection function for successfully designing a clinical trial protocol. To do this, we first introduce a database for a protocol retrieval system constructed from individual protocol data extracted from 184,634 clinical trials and 13,210 frame structures of clinical trial protocols. The database contains a variety of semantic information that allows the filtering of protocols during the search operation. Based on the database, we developed a web application called the clinical trial protocol database system (CLIPS; available at https://corus.kaist.edu/clips). This system enables an interactive search by utilizing protocol elements. To enable an interactive search for combinations of protocol elements, CLIPS provides optional next element selection according to the previous element in the form of a connected tree. The validation results show that our method achieves better performance than that of existing databases in predicting phenotypic features. Public Library of Science 2020-09-18 /pmc/articles/PMC7500653/ /pubmed/32946464 http://dx.doi.org/10.1371/journal.pone.0238290 Text en © 2020 Park et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Park, Junseok Park, Seongkuk Kim, Kwangmin Hwang, Woochang Yoo, Sunyong Yi, Gwan-su Lee, Doheon An interactive retrieval system for clinical trial studies with context-dependent protocol elements |
title | An interactive retrieval system for clinical trial studies with context-dependent protocol elements |
title_full | An interactive retrieval system for clinical trial studies with context-dependent protocol elements |
title_fullStr | An interactive retrieval system for clinical trial studies with context-dependent protocol elements |
title_full_unstemmed | An interactive retrieval system for clinical trial studies with context-dependent protocol elements |
title_short | An interactive retrieval system for clinical trial studies with context-dependent protocol elements |
title_sort | interactive retrieval system for clinical trial studies with context-dependent protocol elements |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500653/ https://www.ncbi.nlm.nih.gov/pubmed/32946464 http://dx.doi.org/10.1371/journal.pone.0238290 |
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