Brain Image Recognition Algorithm and High Performance Computing of Internet of Medical Things Based on Convolutional Neural Network. - Yuxi Liu 003; Jun Xiong (IEEE Access, 2019)

An Interpretable Machine Learning Approach for Predicting Hospital Length of Stay and Readmission. - Yuxi Liu 003; Shaowen Qin (ADMA, 2021)

Modeling long-term dependencies and short-term correlations in patient journey data with temporal attention networks for health prediction. - Yuxi Liu 003; Zhenhao Zhang; Antonio Jimeno-Yepes; Flora D. Salim (BCB, 2022)

Integrated Convolutional and Recurrent Neural Networks for Health Risk Prediction using Patient Journey Data with Many Missing Values. - Yuxi Liu 003; Shaowen Qin; Antonio Jimeno-Yepes; Wei Shao 006; Zhenhao Zhang; Flora D. Salim (BIBM, 2022)

Compound Density Networks for Risk Prediction using Electronic Health Records. - Yuxi Liu 003; Shaowen Qin; Zhenhao Zhang; Wei Shao 006 (BIBM, 2022)

Hospital Readmission Prediction via Personalized Feature Learning and Embedding: A Novel Deep Learning Framework. - Yuxi Liu 003; Shaowen Qin (IEA/AIE, 2022)

Epidemic Modeling of the Spatiotemporal Spread of COVID-19 over an Intercity Population Mobility Network. - Yuxi Liu 003; Shaowen Qin; Zhenhao Zhang (IEA/AIE, 2022)

Compound Density Networks for Risk Prediction using Electronic Health Records. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin (CoRR, 2022)

NeuralHMM: A Deep Markov Network for Health Risk Prediction using Electronic Health Records. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin (IJCNN, 2023)

Deep Imputation-Prediction Networks for Health Risk Prediction using Electronic Health Records. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin (IJCNN, 2023)

Stacked Attention-based Networks for Accurate and Interpretable Health Risk Prediction. - Yuxi Liu 003; Zhenhao Zhang; Campbell Thompson; Richard Leibbrandt; Shaowen Qin; Antonio Jimeno-Yepes (IJCNN, 2023)

Contrastive Learning-Based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling Using EHRs. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin; Flora D. Salim; Antonio Jimeno-Yepes (ECML/PKDD (6), 2023)

Hypergraph Convolutional Networks for Fine-grained ICU Patient Similarity Analysis and Risk Prediction. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin; Flora D. Salim; Antonio Jimeno-Yepes; Jun Shen 001 (CoRR, 2023)

An Analyses of the Impact of Climatic and Environmental Conditions on COVID-19 Prevalence in Epidemic Areas in Australia, South Korea, and Italy. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin; Jun Shen 001; Jiang Bian 001 (ADMA (4), 2024)

Multi-Task Deep Neural Networks for Irregularly Sampled Multivariate Clinical Time Series. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin; Jiang Bian 001 (ICHI, 2024)

A Multi-Graph Fusion Framework for Patient Representation Learning. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin; Flora D. Salim (ICHI, 2024)

Fine-grained Patient Similarity Measuring using Contrastive Graph Similarity Networks. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin; Flora D. Salim; Jiang Bian 001; Antonio Jimeno-Yepes (ICHI, 2024)

Hypergraph Convolutional Networks for Fine-Grained lCU Patient Similarity Analysis and Risk Prediction. - Yuxi Liu 003; Zhenhao Zhang; Shaowen Qin; Flora D. Salim; Antonio Jimeno-Yepes; Jun Shen 001; Jiang Bian 001 (ICHI, 2024)

Boosting Patient Representation Learning via Graph Contrastive Learning. - Zhenhao Zhang; Yuxi Liu 003; Jiang Bian 001; Antonio Jimeno-Yepes; Jun Shen 001; Fuyi Li; Guodong Long; Flora D. Salim (ECML/PKDD (9), 2024)

Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis. - Zhenhao Zhang; Yuxi Liu 003; Meichen Xiao; Kun Wang; Yu Huang 018; Jiang Bian 001; Ruolin Yang 003; Fuyi Li (Briefings Bioinform., 2024)

Variational temporal deconfounder network for individualized treatment effect estimation with longitudinal observational data. - Hao Dai; Yu Huang 018; Yuxi Liu 003; Xing He 003; Jingchuan Guo; Mattia Prosperi; Jiang Bian 001 (J. Biomed. Informatics, 2025)

GatorCLR: Personalized predictions of patient outcomes on electronic health records using self-supervised contrastive graph representation. - Yuxi Liu 003; Zhenhao Zhang; Jiacong Mi; Shirui Pan; Tianlong Chen 001; Yi Guo 005; Xing He 003; Jiang Bian 001 (J. Biomed. Informatics, 2025)

A natural language processing-based approach for early detection of heart failure onset using electronic health records. - Yuxi Liu 003; Zhen Tan 001; Zhenhao Zhang; Song Wang 013; Jingchuan Guo; Huan Liu 001; Tianlong Chen 001; Jiang Bian 001 (Knowl. Based Syst., 2025)

GatorSC: multi-scale cell and gene graphs with mixture-of-experts fusion for single-cell transcriptomics. - Yuxi Liu 003; Zhenhao Zhang; Mufan Qiu; Song Wang 013; Flora D. Salim; Jun Shen 001; Tianlong Chen 001; Imran Razzak; Fuyi Li; Jiang Bian 001 (Briefings Bioinform., 2026)

Identifying Alzheimer's Disease Progression Subphenotypes Via a Graph-based Framework Using Electronic Health Records. - Yu Huang 018; Jie Xu 012; Zhengkang Fan; Yu Hu; Xing He 003; Aokun Chen; Yuxi Liu 003; Rui Yin 002; Jingchuan Guo; Steven T. DeKosky; Michael Jaffee; Manqi Zhou; et al. (J. Heal. Informatics Res., 2026)