Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time
May 21, 2020 Β· Declared Dead Β· π Annual Meeting of the Association for Computational Linguistics
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Benjamin E. Nye, Ani Nenkova, Iain J. Marshall, Byron C. Wallace
arXiv ID
2005.10865
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL,
cs.HC,
cs.LG
Citations
28
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
4 months ago
Abstract
We introduce Trialstreamer, a living database of clinical trial reports. Here we mainly describe the evidence extraction component; this extracts from biomedical abstracts key pieces of information that clinicians need when appraising the literature, and also the relations between these. Specifically, the system extracts descriptions of trial participants, the treatments compared in each arm (the interventions), and which outcomes were measured. The system then attempts to infer which interventions were reported to work best by determining their relationship with identified trial outcome measures. In addition to summarizing individual trials, these extracted data elements allow automatic synthesis of results across many trials on the same topic. We apply the system at scale to all reports of randomized controlled trials indexed in MEDLINE, powering the automatic generation of evidence maps, which provide a global view of the efficacy of different interventions combining data from all relevant clinical trials on a topic. We make all code and models freely available alongside a demonstration of the web interface.
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