20 citations · 21 across the 3 of their papers we have counts for
7 papers
Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health Records
Shuai Niu, Qing Yin, Yunya Song +2
Disease risk prediction has attracted increasing attention in the field of modern healthcare, especially with the latest advances in artificial intelligence (AI). Electronic health…
Self-Supervised Detection of Contextual Synonyms in a Multi-Class Setting: Phenotype Annotation Use Case
Jingqing Zhang, Luis Bolanos, Tong Li +6
Contextualised word embeddings is a powerful tool to detect contextual synonyms. However, most of the current state-of-the-art (SOTA) deep learning concept extraction methods remai…
Bayesian data assimilation for estimating epidemic evolution: a COVID-19 study
Xian Yang, Shuo Wang, Yuting Xing +4
The evolution of epidemiological parameters, such as instantaneous reproduction number Rt, is important for understanding the transmission dynamics of infectious diseases. Current…
A Bayesian Updating Scheme for Pandemics: Estimating the Infection Dynamics of COVID-19
Shuo Wang, Xian Yang, Ling Li +5
Epidemic models play a key role in understanding and responding to the emerging COVID-19 pandemic. Widely used compartmental models are static and are of limited use to evaluate in…
An Epidemiological Modelling Approach for Covid19 via Data Assimilation
Philip Nadler, Shuo Wang, Rossella Arcucci +2
The global pandemic of the 2019-nCov requires the evaluation of policy interventions to mitigate future social and economic costs of quarantine measures worldwide. We propose an ep…
Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records
Jingqing Zhang, Xiaoyu Zhang, Kai Sun +3
The extraction of phenotype information which is naturally contained in electronic health records (EHRs) has been found to be useful in various clinical informatics applications su…