Automated Summarisation for Evidence Based Medicine
March 22, 2012
from 11:00 AM to 12:00 PM
|Where||Marsfield Lecture Theatre|
|Contact Name||Jessie Yin|
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Dr. Diego Mollá Aliod
Thursday 22 March 2012 at 11am
The practice of Evidence Based Medicine (EBM) requires the physician to access the most up to date clinical evidence reported in the medical research literature. However good practice of EBM is seriously affected by the enormous amount of medical literature available and the limited time that the physician has. In this talk I will focus on my research group's current work on natural language processing for EBM. We address the task as one of query-focused multi-document summarisation where a clinical question retrieves several documents, and the clinical evidence must be extracted, summarised and presented in the most effective manner. We have recently gathered a corpus of clinical questions, their evidence summaries, and the related references, and we are currently using it to produce and test various tasks related to the ultimate goal of finding and summarising the evidence.
Dr. Diego Molla-Aliod is a senior lecturer at Macquarie University. His research focuses in query-based information extraction systems. He was the principal researcher in the ExtrAns answer extraction system of unix documentation at University of Zurich, and then the project leader of AnswerFinder, a question-answering system developed at Macquarie University. Since 2009 his research has focused on the medical domain and recently he has made available a corpus for summarisation in evidence based medicine. He is a co-founder and past secretary and president of the Australasian Language Technology Association (ALTA), and was the leader of the Search Technology priority area of the HCSNet ARC Research Network.