[논문]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

doi:10.1371/journal.pone.0238290

[해외논문] An interactive retrieval system for clinical trial studies with context-dependent protocol elements 원문보기

PloS one, v.15 no.9, 2020년, pp.e0238290 -

Park, Junseok (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea) , Park, Seongkuk (Information & Electronics Research Institute, Daejeon, Republic of Korea) , Kim, Kwangmin (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea) , Hwang, Woochang (The Milner Institute, University of Cambridge, Cambridge, United Kingdom) , Yoo, Sunyong (School of Electronics and Computer Engineering, Chonnam National University, Gwangju, Republic of Korea) , Yi, Gwan-su (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea) , Lee, Doheon (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea)

Abstract ▼ AI-Helper

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.

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