Science2Cure: A Clinical Trial Search Prototype

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Abstract

With the advances in precision medicine, identifying clinical trials relevant to a specific patient profile becomes more challenging. Often very specific molecular-level patient features need to be matched for the trial to be deemed relevant. Clinical trials contain strict inclusion and exclusion criteria, often written in free-text. Patients profiles are also semi-structured, with some important information hidden in clinical notes. We present a search system that given a patient profile searches over clinical trials for potential matches. It enables the users to leverage the powerful querying language that comes with Apache Lucene query syntax in combination with state-of-the-art Divergence From Randomness retrieval coupled with a BERT-based neural ranking component. This system aims to assist in clinical decision making.

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Rybinski, M., Karimi, S., & Khoo, A. (2021). Science2Cure: A Clinical Trial Search Prototype. In SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2620–2624). Association for Computing Machinery, Inc. https://doi.org/10.1145/3404835.3462797

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