no code implementations • 15 Sep 2023 • Yikuan Li, Chengsheng Mao, Kaixuan Huang, Hanyin Wang, Zheng Yu, Mengdi Wang, Yuan Luo
Scarcity of health care resources could result in the unavoidable consequence of rationing.
1 code implementation • 26 Aug 2023 • Liang Yao, Jiazhen Peng, Chengsheng Mao, Yuan Luo
Knowledge graphs play a vital role in numerous artificial intelligence tasks, yet they frequently face the issue of incompleteness.
no code implementations • 7 Nov 2022 • Chengsheng Mao, Jie Xu, Luke Rasmussen, Yikuan Li, Prakash Adekkanattu, Jennifer Pacheco, Borna Bonakdarpour, Robert Vassar, Guoqian Jiang, Fei Wang, Jyotishman Pathak, Yuan Luo
Materials and Methods: We identified 3657 patients diagnosed with MCI together with their progress notes from Northwestern Medicine Enterprise Data Warehouse (NMEDW) between 2000-2020.
1 code implementation • 7 May 2022 • Chengsheng Mao, Liang Yao, Yuan Luo
However, few have explored BERT on disease-specific medical domain tasks such as AKI early prediction.
no code implementations • 27 Feb 2022 • Chengsheng Mao, Yuan Luo
Besides the generalizability, by applying an expressive GNN backbone, DP-GNN can also have high expressive power.
1 code implementation • 15 Dec 2020 • Yuan Luo, Chengsheng Mao
We apply genetically motivated constrained tensor factorization to group pathways in a way that reflects molecular mechanism interactions.
1 code implementation • 12 Oct 2020 • Chengsheng Mao, Liang Yao, Yuan Luo
Graph Neural Network (GNN) aggregates the neighborhood of each node into the node embedding and shows its powerful capability for graph representation learning.
3 code implementations • 7 Sep 2019 • Liang Yao, Chengsheng Mao, Yuan Luo
Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness.
Ranked #5 on Link Prediction on UMLS
1 code implementation • 31 Mar 2019 • Chengsheng Mao, Liang Yao, Yuan Luo
In this study, we construct a graph to associate 4 types of medical entities, i. e., patients, encounters, lab tests, and medications, and applied a graph neural network to learn node embeddings for medication recommendation and lab test imputation.
1 code implementation • 31 Mar 2019 • Chengsheng Mao, Liang Yao, Yuan Luo
However, most of the existing approaches for image representation ignore the relations between images and consider each input image independently.
no code implementations • 13 Dec 2018 • Chengsheng Mao, Lijuan Lu, Bin Hu
In this paper, with the insight that the distribution in a local sample space should be simpler than that in the whole sample space, a local probabilistic model established for a local region is expected much simpler and can relax the fundamental assumptions that may not be true in the whole sample space.
no code implementations • 7 Dec 2018 • Chengsheng Mao, Bin Hu, Lei Chen, Philip Moore, Xiaowei Zhang
Additionally, based on the local distribution, we generate a generalized local classification form that can be effectively applied to various datasets through tuning the parameters.
no code implementations • 7 Nov 2018 • Yikuan Li, Liang Yao, Chengsheng Mao, Anand Srivastava, Xiaoqian Jiang, Yuan Luo
We developed data-driven prediction models to estimate the risk of new AKI onset.
no code implementations • 27 Sep 2018 • Guoqing Chao, Chengsheng Mao, Fei Wang, Yuan Zhao, Yuan Luo
We used the simulation data to verify the effectiveness of this method, and then we applied it to ICU mortality risk prediction and demonstrated its superiority over other conventional supervised NMF methods.
no code implementations • 20 Sep 2018 • Chengsheng Mao, Liang Yao, Yuan Luo
In this paper, we recognize that novel classes should be different from each other, and propose distribution networks for open set learning that can model different novel classes based on probability distributions.
1 code implementation • 20 Sep 2018 • Chengsheng Mao, Yiheng Pan, Zexian Zeng, Liang Yao, Yuan Luo
However, most of the previous deep neural network classifiers were based on deterministic architectures which are usually very noise-sensitive and are likely to aggravate the overfitting issue.
9 code implementations • 15 Sep 2018 • Liang Yao, Chengsheng Mao, Yuan Luo
We build a single text graph for a corpus based on word co-occurrence and document word relations, then learn a Text Graph Convolutional Network (Text GCN) for the corpus.
Ranked #6 on Text Classification on Ohsumed
1 code implementation • 17 Jul 2018 • Himanshu Sharma, Chengsheng Mao, Yizhen Zhang, Haleh Vatani, Liang Yao, Yizhen Zhong, Luke Rasmussen, Guoqian Jiang, Jyotishman Pathak, Yuan Luo
Our system facilitates portable phenotyping of obesity and its 15 comorbidities based on the unstructured patient discharge summaries, while achieving a performance that often ranked among the top 10 of the challenge participants.
no code implementations • 17 Jul 2018 • Liang Yao, Chengsheng Mao, Yuan Luo
Clinical text classification is an important problem in medical natural language processing.
Ranked #2 on Clinical Note Phenotyping on I2B2 2008: Obesity