Liyuan Zhou

Learn More
BACKGROUND Preeclampsia is known to be associated with reduced circulating levels of estrogen. The effects of estrogen in preeclampsia are normally mediated by the classical estrogen receptors. Intriguingly, a novel estrogen receptor, G protein-coupled receptor 30 (GPR30), has been recently found to play an important role in several estrogenic effects.(More)
BACKGROUND Over a tenth of preventable adverse events in health care are caused by failures in information flow. These failures are tangible in clinical handover; regardless of good verbal handover, from two-thirds to all of this information is lost after 3-5 shifts if notes are taken by hand, or not at all. Speech recognition and information extraction(More)
Word embeddings – distributed word representations that can be learned from un-labelled data – have been shown to have high utility in many natural language processing applications. In this paper, we perform an extrinsic evaluation of five popular word embedding methods in the context of four sequence labelling tasks: POS-tagging, syntactic chunking, NER(More)
Word embeddings – distributed word representations that can be learned from un-labelled data – have been shown to have high utility in many natural language processing applications. In this paper, we perform an extrinsic evaluation of five popular word embedding methods in the context of four sequence labelling tasks: POS-tagging, syntactic chunking, NER(More)
OBJECTIVE We study the use of speech recognition and information extraction to generate drafts of Australian nursing-handover documents. METHODS Speech recognition correctness and clinicians' preferences were evaluated using 15 recorder-microphone combinations, six documents, three speakers, Dragon Medical 11, and five survey/interview participants.(More)
Cascaded speech recognition (SR) and information extraction (IE) could support the best practice for clinical handover and release clinicians' time from writing documents to patient interaction and education. However, high requirements for processing correctness evoke methodological challenges and hence, processing correctness needs to be carefully(More)
During clinical handover, clinicians exchange information about the patients and the state of clinical management. To improve care safety and quality, both handover and its documentation have been standardized. Speech recognition and entity extraction provide a way to help health service providers to follow these standards by implementing the handover(More)
Polysaccharides from edible fungi usually exhibit many bioactivities. Our previous studies found that polysaccharide TLH-3 extracted from Tricholoma lobayense possessed noticeable antioxidant activity. To further explore its biological activities, the antioxidant and anti-aging activities of TLH-3 were evaluated in vitro and in vivo. The results of(More)
In named entity recognition, we often don't have a large in-domain training corpus or a knowledge base with adequate coverage to train a model directly. In this paper, we propose a method where, given training data in a related domain with similar (but not identical) named entity (NE) types and a small amount of in-domain training data, we use transfer(More)