160 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National University of SingaporeSG17 papers
- Duke-NUS Medical SchoolSG16 papers
- Duke UniversityUS13 papers
- SingHealthSG11 papers
- Agency for Science, Technology and ResearchSG6 papers
- Institute of Data ScienceSG6 papers
- Nanyang Technological UniversitySG5 papers
- Institute of High Performance ComputingSG4 papers
- Imperial College LondonGB3 papers
- Institute for Infocomm ResearchSG3 papers
- Columbia UniversityUS2 papers
- Data Storage InstituteSG2 papers
6 papers · 1 filter
Benchmarking emergency department triage prediction models with machine learning and large public electronic health records
Feng Xie, Jun Zhou, Jin Wee Lee +10
The demand for emergency department (ED) services is increasing across the globe, particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have become…
Multi-Slice Dense-Sparse Learning for Efficient Liver and Tumor Segmentation
Ziyuan Zhao, Zeyu Ma, Yanjie Liu +2
Accurate automatic liver and tumor segmentation plays a vital role in treatment planning and disease monitoring. Recently, deep convolutional neural network (DCNNs) has obtained tr…
Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation
Mengya Xu, Mobarakol Islam, Chwee Ming Lim +1
Generating surgical reports aimed at surgical scene understanding in robot-assisted surgery can contribute to documenting entry tasks and post-operative analysis. Despite the impre…
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies
Feng Xie, Han Yuan, Yilin Ning +5
Objective: Temporal electronic health records (EHRs) can be a wealth of information for secondary uses, such as clinical events prediction or chronic disease management. However, c…
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data
Han Yuan, Feng Xie, Marcus Eng Hock Ong +7
Background: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among a wide variety of decision-making models for determining the…
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data
Feng Xie, Yilin Ning, Han Yuan +4
Scoring systems are highly interpretable and widely used to evaluate time-to-event outcomes in healthcare research. However, existing time-to-event scores are predominantly created…