11 citations · 32 across the 8 of their papers we have counts for
8 papers
Resolving the bias-precision paradox with stochastic causal representation learning for personalized medicine
Peisong Zhang, Manqiang Peng, Yuxuan Wu +21
Estimating individualized treatment effects from longitudinal observational data is central to data-driven medicine, yet existing methods face a fundamental limitation: reducing co…
AI-generated data contamination erodes pathological variability and diagnostic reliability
Hongyu He, Shaowen Xiang, Ye Zhang +15
Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content, creating a feedback loop where future models are increasingly at risk of train…
HoloPOCUS: Portable Mixed-Reality 3D Ultrasound Tracking, Reconstruction and Overlay
Kian Wei Ng, Yujia Gao, Shaheryar Mohammed Furqan +4
Ultrasound (US) imaging provides a safe and accessible solution to procedural guidance and diagnostic imaging. The effective usage of conventional 2D US for interventional guidance…
MLCask: Efficient Management of Component Evolution in Collaborative Data Analytics Pipelines
Zhaojing Luo, Sai Ho Yeung, Meihui Zhang +7
With the ever-increasing adoption of machine learning for data analytics, maintaining a machine learning pipeline is becoming more complex as both the datasets and trained models e…
TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications
Kaiping Zheng, Shaofeng Cai, Horng Ruey Chua +3
In high stakes applications such as healthcare and finance analytics, the interpretability of predictive models is required and necessary for domain practitioners to trust the pred…
Deep Reinforcement Learning for Clinical Decision Support: A Brief Survey
Siqi Liu, Kee Yuan Ngiam, Mengling Feng
Owe to the recent advancements in Artificial Intelligence especially deep learning, many data-driven decision support systems have been implemented to facilitate medical doctors in…
A Self-Correcting Deep Learning Approach to Predict Acute Conditions in Critical Care
Ziyuan Pan, Hao Du, Kee Yuan Ngiam +3
In critical care, intensivists are required to continuously monitor high dimensional vital signs and lab measurements to detect and diagnose acute patient conditions. This has alwa…
Medical Concept Embedding with Time-Aware Attention
Xiangrui Cai, Jinyang Gao, Kee Yuan Ngiam +3
Embeddings of medical concepts such as medication, procedure and diagnosis codes in Electronic Medical Records (EMRs) are central to healthcare analytics. Previous work on medical…