A clinical trial protocol defines the procedural methods that should be performed during a clinical trial. Every clinical trial starts with the design of its protocol. In designing the protocol, it is common for researchers to refer to electronic databases and extract protocol elements from clinical trial information by using a keyword search. However, state-of-the-art retrieval systems only offer text-based searches based on user-entered keywords. In this paper, we present an interactive retrieval system with a context-dependent protocol-element-selection system for the successful designing of a clinical trial protocol. In addition, we introduce a database for a protocol retrieval system constructed from a combined element analysis. The database is built using individual protocol data extracted from 184,634 clinical trials and provides 13,210 integrated structural data points. Furthermore, the database contains various semantic information that enables the protocols to be filtered during the search operation.Moreover, we developed a web application called the clinical trial protocol database system (CLIPS; available at https://corus.kaist.edu/clips), which enables an interactive search based on protocol elements. CLIPS provides options to select the next element according to the previous element in the form of a connected tree, thus enabling an interactive search for combinations of protocol elements. The results of technical validation show that our method achieves better performance than existing databases in predicting phenotypic features.
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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