8 papers
Paragraph-level Simplification of Medical Texts
Ashwin Devaraj, Iain J. Marshall, Byron C. Wallace +1
We consider the problem of learning to simplify medical texts. This is important because most reliable, up-to-date information in biomedicine is dense with jargon and thus practica…
Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization
Byron C. Wallace, Sayantan Saha, Frank Soboczenski +1
We consider the problem of automatically generating a narrative biomedical evidence summary from multiple trial reports. We evaluate modern neural models for abstractive summarizat…
Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time
Benjamin E. Nye, Ani Nenkova, Iain J. Marshall +1
We introduce Trialstreamer, a living database of clinical trial reports. Here we mainly describe the evidence extraction component; this extracts from biomedical abstracts key piec…
Evidence Inference 2.0: More Data, Better Models
Jay DeYoung, Eric Lehman, Ben Nye +2
How do we most effectively treat a disease or condition? Ideally, we could consult a database of evidence gleaned from clinical trials to answer such questions. Unfortunately, no s…
Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding
Gaurav Singh, James Thomas, Iain J. Marshall +2
We propose a model for tagging unstructured texts with an arbitrary number of terms drawn from a tree-structured vocabulary (i.e., an ontology). We treat this as a special case of…
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature
Benjamin Nye, Junyi Jessy Li, Roma Patel +4
We present a corpus of 5,000 richly annotated abstracts of medical articles describing clinical randomized controlled trials. Annotations include demarcations of text spans that de…