Few-Shot Relation Extraction With Dual Graph Neural Network Interaction.

Recent advances in relation extraction with deep neural architectures have achieved excellent performance. However, current models still suffer from two main drawbacks: 1) they require enormous volumes of training data to avoid model overfitting and 2) there is a sharp decrease in performance when the data distribution during training and testing shift from one domain to the other. It is thus vital to reduce the data requirement in training and explicitly model the distribution difference when transferring knowledge from one domain to another.

A neural classification method for supporting the creation of BioVerbNet.

Background: VerbNet, an extensive computational verb lexicon for English, has proved useful for supporting a wide range of Natural Language Processing tasks requiring information about the behaviour and meaning of verbs. Biomedical text processing and mining could benefit from a similar resource. We take the first step towards the development of BioVerbNet: A VerbNet specifically aimed at describing verbs in the area of biomedicine.

Bio-SimVerb and Bio-SimLex: wide-coverage evaluation sets of word similarity in biomedicine.

Background: Word representations support a variety of Natural Language Processing (NLP) tasks. The quality of these representations is typically assessed by comparing the distances in the induced vector spaces against human similarity judgements. Whereas comprehensive evaluation resources have recently been developed for the general domain, similar resources for biomedicine currently suffer from the lack of coverage, both in terms of word types included and with respect to the semantic distinctions.

A neural network multi-task learning approach to biomedical named entity recognition.

Background: Named Entity Recognition (NER) is a key task in biomedical text mining. Accurate NER systems require task-specific, manually-annotated datasets, which are expensive to develop and thus limited in size. Since such datasets contain related but different information, an interesting question is whether it might be possible to use them together to improve NER performance.

Detection and management of depression in adult primary care patients in Hong Kong: a cross-sectional survey conducted by a primary care practice-based research network.

Background: This study aimed to examine the prevalence, risk factors, detection rates and management of primary care depression in Hong Kong.

Methods: A cross-sectional survey containing the PHQ-9 instrument was conducted on waiting room patients of 59 primary care doctors. Doctors blinded to the PHQ-9 scores reported whether they thought their patients had depression and their management.

Validation of the Chinese Handwriting Analysis System (CHAS) for primary school students in Hong Kong.

There are more children diagnosed with specific learning difficulties in recent years as people are more aware of these conditions. Diagnostic tool has been validated to screen out this condition from the population (SpLD test for Hong Kong children). However, for specific assessment on handwriting problem, there seems a lack of standardized and objective evaluation tool to look into the problems.

The epidemiology and natural history of depressive disorders in Hong Kong's primary care.

Background: Depressive disorders are commonly managed in primary care and family physicians are ideally placed to serve as central providers to these patients. Around the world, the prevalence of depressive disorders in patients presenting to primary care is between 10-20%, of which around 50% remain undiagnosed. In Hong Kong, many barriers exist preventing the optimal treatment and management of patients with depressive disorders.

Facemasks and hand hygiene to prevent influenza transmission in households: a cluster randomized trial.

Background: Few data are available about the effectiveness of nonpharmaceutical interventions for preventing influenza virus transmission.

Objective: To investigate whether hand hygiene and use of facemasks prevents household transmission of influenza.

Design: Cluster randomized, controlled trial.

Preliminary findings of a randomized trial of non-pharmaceutical interventions to prevent influenza transmission in households.

Background: There are sparse data on whether non-pharmaceutical interventions can reduce the spread of influenza. We implemented a study of the feasibility and efficacy of face masks and hand hygiene to reduce influenza transmission among Hong Kong household members.

Methodology/principal Findings: We conducted a cluster randomized controlled trial of households (composed of at least 3 members) where an index subject presented with influenza-like-illness of <48 hours duration.