160 citations · 218 across the 13 of their papers we have counts for
5 papers · 1 filter
Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
Xiang Lan, Hanshu Yan, Shenda Hong +1
Not all positive pairs are beneficial to time series contrastive learning. In this paper, we study two types of bad positive pairs that can impair the quality of time series repres…
Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals
Xiang Lan, Dianwen Ng, Shenda Hong +1
Learning information-rich and generalizable representations effectively from unlabeled multivariate cardiac signals to identify abnormal heart rhythms (cardiac arrhythmias) is valu…
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…
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…