Patient-Centered Clinical Trials Decision Support using Linked Open Data

Author:

MacKellar Bonnie1,Schweikert Christina1,Chun Soon Ae2

Affiliation:

1. Division of Computer Science, Mathematics and Science, St John's University, Queens, NY, USA

2. Computer Science, Graduate Center of Information Systems and Informatics, College of Staten Island, City University of New York, New York, NY, USA

Abstract

Patients often want to participate in relevant clinical trials for new or more effective alternative treatments. The clinical search system made available by the NIH is a step forward to support the patient's decision making, but, it is difficult to use and requires the patient to sift through lengthy text descriptions for relevant information. In addition, patients deciding whether to pursue a given trial often want more information, such as drug information. The authors' overall aim is to develop an intelligent patient-centered clinical trial decision support system. Their approach is to integrate Open Data sources related to clinical trials using the Semantic Web's Linked Data framework. The linked data representation, in terms of RDF triples, allows the development of a clinical trial knowledge base that includes entities from different open data sources and relationships among entities. The authors consider Open Data sources such as clinical trials provided by NIH as well as the drug side effects dataset SIDER. The authors use UMLS (Unified Medical Language System) to provide consistent semantics and ontological knowledge for clinical trial related entities and terms. The authors' semantic approach is a step toward a cognitive system that provides not only patient-centered integrated data search but also allows automated reasoning in search, analysis and decision making using the semantic relationships embedded in the Linked data. The authors present their integrated clinical trial knowledge base development and a prototype, patient-centered Clinical Trial Decision Support System that include capabilities of semantic search and query with reasoning ability, and semantic-link browsing where an exploration of one concept leads to other concepts easily via links which can provide visual search for the end users.

Publisher

IGI Global

Subject

Pharmacology (medical)

Reference36 articles.

1. Semantically-enabled Intelligent Patient Recruitment in Clinical Trials

2. An overview of MetaMap: Historical perspective and recent advances.;A. R.Aronson;JAMIA: Journal of the American Medical Informatics Association,2010

3. Using the Internet to search for cancer clinical trials: A comparative audit of clinical trial search tools

4. Berners-Lee, T. (2006). Linked data - Design issues. Retrieved March 1, 2013, http://www.w3.org/DesignIssues/LinkedData.html

5. Using Semantic Web Technologies for Clinical Trial Recruitment

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