no code implementations • 4 Mar 2024 • Ziwen Wang, Jin Wee Lee, Tanujit Chakraborty, Yilin Ning, Mingxuan Liu, Feng Xie, Marcus Eng Hock Ong, Nan Liu
The calibration of DeepSurv (IBS: 0. 041) performed the best, followed by RSF (IBS: 0. 042) and GBM (IBS: 0. 0421), all using the full variables.
1 code implementation • 8 Nov 2023 • Feng Xie, Xin Song, Xiang Zeng, Xuechen Zhao, Lei Tian, Bin Zhou, Yusong Tan
More importantly, in pseudo mapping learning, we propose a bi-directional voting (BDV) strategy that fuses the alignment decisions in different directions to estimate the uncertainty via the joint matching confidence score.
no code implementations • 13 Aug 2023 • Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang
To address this, we propose a Generalized Independent Noise (GIN) condition for linear non-Gaussian acyclic causal models that incorporate latent variables, which establishes the independence between a linear combination of certain measured variables and some other measured variables.
1 code implementation • 28 Apr 2023 • Feng Xie, Xiang Zeng, Bin Zhou, Yusong Tan
Entity alignment (EA) which links equivalent entities across different knowledge graphs (KGs) plays a crucial role in knowledge fusion.
no code implementations • 14 Apr 2023 • Siqi Li, Pinyan Liu, Gustavo G. Nascimento, Xinru Wang, Fabio Renato Manzolli Leite, Bibhas Chakraborty, Chuan Hong, Yilin Ning, Feng Xie, Zhen Ling Teo, Daniel Shu Wei Ting, Hamed Haddadi, Marcus Eng Hock Ong, Marco Aurélio Peres, Nan Liu
Structured data, one of the most prevalent forms of clinical data, has experienced significant growth in volume concurrently, notably with the widespread adoption of electronic health records in clinical practice.
1 code implementation • 1 Mar 2023 • Siqi Li, Yilin Ning, Marcus Eng Hock Ong, Bibhas Chakraborty, Chuan Hong, Feng Xie, Han Yuan, Mingxuan Liu, Daniel M. Buckland, Yong Chen, Nan Liu
We also calculated the average AUC values and SDs for each local model, and the FedScore model showed promising accuracy and stability with a high average AUC value which was closest to the one of the pooled model and SD which was lower than that of most local models.
no code implementations • 15 Oct 2022 • Mingxuan Liu, Siqi Li, Han Yuan, Marcus Eng Hock Ong, Yilin Ning, Feng Xie, Seyed Ehsan Saffari, Victor Volovici, Bibhas Chakraborty, Nan Liu
We found that model backbone(s) differed among data types as well as the imputation strategy.
no code implementations • 7 Oct 2022 • Xuechen Zhao, Jiaying Zou, Zhong Zhang, Feng Xie, Bin Zhou, Lei Tian
In this work, we propose a stance detection approach that can efficiently adapt to unseen targets, the core of which is to capture target-invariant syntactic expression patterns as transferable knowledge.
no code implementations • 1 Oct 2022 • Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
Most causal discovery procedures assume that there are no latent confounders in the system, which is often violated in real-world problems.
1 code implementation • 10 Sep 2022 • Feng Xie, Zhong Zhang, Xuechen Zhao, Haiyang Wang, Jiaying Zou, Lei Tian, Bin Zhou, Yusong Tan
The ongoing COVID-19 pandemic has caused immeasurable losses for people worldwide.
1 code implementation • 23 Aug 2022 • Feng Xie, Zhong Zhang, Liang Li, Bin Zhou, Yusong Tan
Epidemic forecasting is the key to effective control of epidemic transmission and helps the world mitigate the crisis that threatens public health.
1 code implementation • 23 Aug 2022 • Feng Xie, Zhong Zhang, Xuechen Zhao, Bin Zhou, Yusong Tan
In Inter-Series Embedding Module, a multi-scale unified convolution component called Region-Aware Convolution is proposed, which cooperates with self-attention to capture dynamic dependencies between time series obtained from multiple regions.
1 code implementation • 10 Jan 2022 • Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie, Bibhas Chakraborty, Daniel Shu Wei Ting, Nan Liu
Risk scores are widely used for clinical decision making and commonly generated from logistic regression models.
1 code implementation • 22 Nov 2021 • Feng Xie, Jun Zhou, Jin Wee Lee, Mingrui Tan, Siqi Li, Logasan S/O Rajnthern, Marcel Lucas Chee, Bibhas Chakraborty, An-Kwok Ian Wong, Alon Dagan, Marcus Eng Hock Ong, Fei Gao, Nan Liu
In this paper, based on the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database, we developed a publicly available benchmark suite for ED triage predictive models and created a benchmark dataset that contains over 400, 000 ED visits from 2011 to 2019.
no code implementations • 21 Jul 2021 • Feng Xie, Han Yuan, Yilin Ning, Marcus Eng Hock Ong, Mengling Feng, Wynne Hsu, Bibhas Chakraborty, Nan Liu
To some extent, current deep learning solutions can address these challenges.
1 code implementation • 13 Jul 2021 • Han Yuan, Feng Xie, Marcus Eng Hock Ong, Yilin Ning, Marcel Lucas Chee, Seyed Ehsan Saffari, Hairil Rizal Abdullah, Benjamin Alan Goldstein, Bibhas Chakraborty, Nan Liu
All scoring models were evaluated on the basis of their area under the curve (AUC) in the receiver operating characteristic analysis and balanced accuracy (i. e., mean value of sensitivity and specificity).
1 code implementation • 13 Jun 2021 • Feng Xie, Yilin Ning, Han Yuan, Benjamin Alan Goldstein, Marcus Eng Hock Ong, Nan Liu, Bibhas Chakraborty
We illustrated our method in a real-life study of 90-day mortality of patients in intensive care units and compared its performance with survival models (i. e., Cox) and the random survival forest.
BIG-bench Machine Learning Interpretable Machine Learning +1
no code implementations • NeurIPS 2020 • Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang
Despite its success in certain domains, most existing methods focus on causal relations between observed variables, while in many scenarios the observed ones may not be the underlying causal variables (e. g., image pixels), but are generated by latent causal variables or confounders that are causally related.
no code implementations • 19 Sep 2020 • Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao
In this paper, we propose Multi-Domain Linear Non-Gaussian Acyclic Models for Latent Factors (MD-LiNA), where the causal structure among latent factors of interest is shared for all domains, and we provide its identification results.
no code implementations • NeurIPS 2019 • Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang
In this paper, by properly leveraging the non-Gaussianity of the data, we propose to estimate the structure over latent variables with the so-called Triad constraints: we design a form of "pseudo-residual" from three variables, and show that when causal relations are linear and noise terms are non-Gaussian, the causal direction between the latent variables for the three observed variables is identifiable by checking a certain kind of independence relationship.
no code implementations • 8 Mar 2019 • Dong-dong Zhang, Lei Zhang, Vladimir Zaborovsky, Feng Xie, Yan-wen Wu, Ting-ting Lu
During the rapid urbanization construction of China, acquisition of urban geographic information and timely data updating are important and fundamental tasks for the refined management of cities.