Doctoral student Linh Hoang will present a rehearsal of her iConference paper, "Opportunities for computer support for systematic reviewing - a gap analysis."
Abstract: Systematic review is a type of literature review designed to synthesize all available evidence on a given question. Systematic reviews require significant time and effort, which has led to the continuing development of algorithms and computer support tools. This paper seeks to identify the gaps and opportunities for computer support. By interviewing experienced systematic reviewers, we identify the technical problems and challenges reviewers face in conducting a systematic review and the current uses of computer support. We propose potential research directions for how computer support could help to speed the systematic review process while retaining or improving review quality.
Hoang is a second year PhD student at the iSchool. She is motivated to build smarter information systems that can help people get insights from data and make important decisions, without the hassle of going through the laborious work of collecting and disambiguating knowledge. Currently she is working on information extraction from medical research papers, including studying the systematic review process and proposing how text mining and machine learning techniques can automatically extract important data elements from clinical trial reports. As part of the NIH-funded project, "Text Mining Pipeline to Accelerate Systematic Reviews in Evidence-Based Medicine," she is evaluating Metta – a meta-search engine for finding articles in medical literatures and RCT Tagger – an automated RCT tagger for identifying human randomized controlled clinical trial articles. Her research interests include information extraction, knowledge discovery, and data analytics.
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