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• W155335823 abstract "Discovering the network of associations and relationships among diseases, genes, and risk factors is critical in clinical and translational research. The goal of this study was to design a system that would enable strategic reading/filtering and reduce information overload, generate new hypotheses, bridge the knowledge gap, and develop “smart apps.” We present the implementation of a text analytic system, Adaptive Robust and Integrative Analysis for Finding Novel Associations (ARIANA). The system is context-specific, modular, and scalable and able to capture direct and indirect associations among 2,545 biomedical concepts. An easy-to-use Web interface was developed to query, interact, and visualize the results. Empirical studies showed that the system was able to find novel associations and generate new hypotheses. For instance, the system captured the association between the drug hexamethonium and pulmonary fibrosis, which in 2001 caused the tragic death of a healthy volunteer. The software is available with a properly executed end-user licensing agreement at http://www.ARIANAmed.org." @default.
• W155335823 created "2016-06-24" @default.
• W155335823 creator A5002765080 @default.
• W155335823 creator A5057855237 @default.
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• W155335823 date "2015-01-01" @default.
• W155335823 modified "2023-09-27" @default.
• W155335823 title "Literature Mining and Ontology Mapping Applied to Big Data" @default.
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• W155335823 doi "https://doi.org/10.1016/b978-0-12-801967-2.00013-6" @default.
• W155335823 hasPublicationYear "2015" @default.
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