Automating Biomedical Evidence Synthesis: RobotReviewer
| Autor: | Joël Kuiper, Edward Banner, Byron C. Wallace, Iain J. Marshall |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry MEDLINE 02 engineering and technology computer.software_genre Article 3. Good health law.invention 03 medical and health sciences 0302 clinical medicine Randomized controlled trial law 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 030212 general & internal medicine Artificial intelligence business computer Reliability (statistics) Evidence synthesis Natural language processing |
| Zdroj: | ACL (System Demonstrations) King's College London |
| Popis: | We present RobotReviewer, an open-source web-based system that uses machine learning and NLP to semi-automate biomedical evidence synthesis, to aid the practice of Evidence-Based Medicine. RobotReviewer processes full-text journal articles (PDFs) describing randomized controlled trials (RCTs). It appraises the reliability of RCTs and extracts text describing key trial characteristics (e.g., descriptions of the population) using novel NLP methods. RobotReviewer then automatically generates a report synthesising this information. Our goal is for RobotReviewer to automatically extract and synthesise the full-range of structured data needed to inform evidence-based practice. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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