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One of the tasks a Clinical Decision Support (CDS) system is designed to solve is retrieving the most relevant and actionable literature for a given medical case report. In this work, we present a query reformulation approach that addresses the unique formulation of case reports, making them suitable to be used on a general purpose search engine.(More)
Keeping current given the vast volume of medical literature published yearly poses a serious challenge for medical professionals. Thus, interest in systems that aid physicians in making clinical decisions is intensifying. A task of Clinical Decision Support (CDS) systems is retrieving highly relevant medical literature that could help healthcare(More)
Online mental health forums provide users with an anonymous support platform that is facilitated by moderators responsible for finding and addressing critical posts, especially those related to self-harm. Given the seriousness of these posts, it is important that the moderators are able to locate these critical posts quickly in order to respond with timely(More)
We propose a summarization approach for scientific articles which takes advantage of citation-context and the document discourse model. While citations have been previously used in generating scientific summaries, they lack the related context from the referenced article and therefore do not accurately reflect the article’s content. Our method overcomes the(More)
Extraction and interpretation of temporal information from clinical text is essential for clinical practitioners and researchers. SemEval 2016 Task 12 (Clinical TempEval) addressed this challenge using the THYME1 corpus, a corpus of clinical narratives annotated with a schema based on TimeML2 guidelines. We developed and evaluated approaches for: extraction(More)
Clinical TempEval 2017 (SemEval 2017 Task 12) addresses the task of crossdomain temporal extraction from clinical text. We present a system for this task that uses supervised learning for the extraction of temporal expression and event spans with corresponding attributes and narrative container relations. Approaches include conditional random fields and(More)
Citation sentences (citances) to a reference article have been extensively studied for summarization tasks. However, citances might not accurately represent the content of the cited article, as they often fail to capture the context of the reported findings and can be affected by epistemic value drift. Following the intuition behind the TAC (Text Analysis(More)
Recent interest in search tools for Clinical Decision Support (CDS) has dramatically increased. These tools help clinicians assess a medical situation by providing actionable information in the form of a select few highly relevant recent medical papers. Unlike traditional search, which is designed to deal with short queries, queries in CDS are long and(More)
Medical errors are leading causes of death in the US and as such, prevention of these errors is paramount to promoting healthcare. Patient Safety Event reports are narratives describing potential adverse events to the patients and are important in identifying, and preventing medical errors. We present a neural network architecture for identifying the type(More)