Evidence Inference 2.0: More Data, Better Models
| Autor: | Benjamin E. Nye, Byron C. Wallace, Eric Lehman, Iain J. Marshall, Jay DeYoung |
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| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Computation and Language Information retrieval Computer science business.industry Inference 010501 environmental sciences 01 natural sciences 3. Good health Task (project management) Clinical trial 03 medical and health sciences 0302 clinical medicine Systematic review Documentation Health care 030212 general & internal medicine business Computation and Language (cs.CL) Natural language 0105 earth and related environmental sciences Medical literature |
| Zdroj: | BioNLP |
| DOI: | 10.48550/arxiv.2005.04177 |
| Popis: | 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 such database exists; clinical trial results are instead disseminated primarily via lengthy natural language articles. Perusing all such articles would be prohibitively time-consuming for healthcare practitioners; they instead tend to depend on manually compiled systematic reviews of medical literature to inform care. NLP may speed this process up, and eventually facilitate immediate consult of published evidence. The Evidence Inference dataset was recently released to facilitate research toward this end. This task entails inferring the comparative performance of two treatments, with respect to a given outcome, from a particular article (describing a clinical trial) and identifying supporting evidence. For instance: Does this article report that chemotherapy performed better than surgery for five-year survival rates of operable cancers? In this paper, we collect additional annotations to expand the Evidence Inference dataset by 25\%, provide stronger baseline models, systematically inspect the errors that these make, and probe dataset quality. We also release an abstract only (as opposed to full-texts) version of the task for rapid model prototyping. The updated corpus, documentation, and code for new baselines and evaluations are available at http://evidence-inference.ebm-nlp.com/. Comment: Accepted as workshop paper into BioNLP Updated results from SciBERT to Biomed RoBERTa |
| Databáze: | OpenAIRE |
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