Feifan Liu

TL;DR: The results have shown that the simple unsupervised TFIDF approach performs reasonably well, and the additional information from POS and sentence score helps keyword extraction, however, the graph method is less effective for this domain.

TL;DR: A clinical question answering system named AskHERMES is built to perform robust semantic analysis on complex clinical questions and output question-focused extractive summaries as answers and demonstrates the potential to outperform both Google and UpToDate systems.

TL;DR: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging, and text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results.

TL;DR: Evaluating teams using the gold standard and inferred ground truth shows that the EM algorithm allows team submissions to be differentiated while keeping the manual annotation effort feasible, and shows measures of comparative performance between teams.

TL;DR: MADE results show that recent progress in NLP has led to remarkable improvements in NER and RI tasks for the clinical domain, however, some room for improvement remains, particularly in the NER-RI task.