Jie Xu

According to our database, Jie Xu authored at least 36 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

Chang Su, Yu Hou, Jielin Xu, Zhenxing Xu, Manqi Zhou, Alison Ke, Haoyang Li, Jie Xu, Matthew Brendel, Jacqueline R. M. A. Maasch, Zilong Bai, Haotan Zhang, Yingying Zhu, Molly C. Cincotta, Xinghua Shi, Claire Henchcliffe, James B. Leverenz, Jeffrey Cummings, Michael S. Okun, Jiang Bian, Feixiong Cheng, Fei Wang

npj Digit. Medicine, 2024

Beyond Skip Connection: Pooling and Unpooling Design for Elimination Singularities.

Chengkun Sun, Jinqian Pan, Juoli Jin, Russell Terry, Jiang Bian, Jie Xu

CoRR, 2024

BGDB: Bernoulli-Gaussian Decision Block with Improved Denoising Diffusion Probabilistic Models.

Chengkun Sun, Jinqian Pan, Russell Terry, Jiang Bian, Jie Xu

CoRR, 2024

Towards Clinical AI Fairness: Filling Gaps in the Puzzle.

Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Xiaoxuan Liu, Mayli Mertens, Yuqing Shang, Xin Li, Di Miao, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Narrendar RaviChandran, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu

CoRR, 2024

2023

AD-BERT: Using pre-trained language model to predict the progression from mild cognitive impairment to Alzheimer's disease.

Chengsheng Mao, Jie Xu, Luke V. Rasmussen, Yikuan Li, Prakash Adekkanattu, Jennifer A. Pacheco, Borna Bonakdarpour, Robert Vassar, Li Shen, Guoqian Jiang, Fei Wang, Jyotishman Pathak, Yuan Luo

J. Biomed. Informatics, August, 2023

A translational perspective towards clinical AI fairness.

Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Mayli Mertens, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Ravi Chandran Narrendar, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu

npj Digit. Medicine, 2023

Classification of Benign and Malignant Renal Tumors Based on CT Scans and Clinical Data Using Machine Learning Methods.

Jie Xu, Xing He, Wei Shao, Jiang Bian, Russell Terry

Informatics, 2023

Assess the documentation of cognitive tests and biomarkers in electronic health records via natural language processing for Alzheimer's disease and related dementias.

Zhaoyi Chen, Hansi Zhang, Xi Yang, Songzi Wu, Xing He, Jie Xu, Jingchuan Guo, Mattia Prosperi, Fei Wang, Hua Xu, Yong Chen, Hui Hu, Steven DeKosky, Matthew Farrer, Yi Guo, Yonghui Wu, Jiang Bian

Int. J. Medical Informatics, 2023

Towards clinical AI fairness: A translational perspective.

Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Mayli Mertens, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Ravi Chandran Narrendar, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu

CoRR, 2023

Quantification of Racial Disparity on Urinary Tract Infection Recurrence and Treatment Resistance in Florida using Algorithmic Fairness Methods.

Inyoung Jun, Sarah E. S. Leary, Jie Xu, Jiang Bian, Mattia Prosperi

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

2022

A(DP)²2SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent With Differential Privacy.

Jie Xu, Wei Zhang, Fei Wang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Design and validation of a FHIR-based EHR-driven phenotyping toolbox.

Pascal S. Brandt, Jennifer A. Pacheco, Prakash Adekkanattu, Evan Sholle, Sajjad Abedian, Daniel J. Stone, David Knaack, Jie Xu, Zhenxing Xu, Yifan Peng, Natalie C. Benda, Fei Wang, Yuan Luo, Guoqian Jiang, Jyotishman Pathak, Luke V. Rasmussen

J. Am. Medical Informatics Assoc., 2022

AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease.

Chengsheng Mao, Jie Xu, Luke V. Rasmussen, Yikuan Li, Prakash Adekkanattu, Jennifer A. Pacheco, Borna Bonakdarpour, Robert Vassar, Guoqian Jiang, Fei Wang, Jyotishman Pathak, Yuan Luo

CoRR, 2022

Identification of Social and Racial Disparities in Risk of HIV Infection in Florida using Causal AI Methods.

Mattia Prosperi, Jie Xu, Jingchuan Serena Guo, Jiang Bian, Wei-Han William Chen, Shantrel Canidate, Simone Marini, Mo Wang

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

Federated Learning for Healthcare Informatics.

Jie Xu, Benjamin S. Glicksberg, Chang Su, Peter B. Walker, Jiang Bian, Fei Wang

J. Heal. Informatics Res., 2021

A Deep Learning Framework Using a Pre-trained BERT Model to Predict the Risk of Progression from Mild Cognitive Impairment to Alzheimer's Disease.

Chengsheng Mao, Jie Xu, Luke V. Rasmussen, Jennifer A. Pacheco, Guoqian Jiang, Fei Wang, Richard Isaacson, Jyotishman Pathak, Yuan Luo

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

Multi-site Evaluation of Longitudinal Changes in Ejection Fraction in Heart Failure Patients Through Data-driven Phenotyping.

Prakash Adekkanattu, Jennifer A. Pacheco, Joseph Kabariti, Daniel J. Stone, Yue Yu, Parag Goyal, Faraz S. Ahmad, Guoqian Jiang, Yuan Luo, Luke V. Rasmussen, Pascal S. Brandt, Zhenxing Xu, Jie Xu, Fei Wang, Natalie C. Benda, Thomas R. Campion Jr., Jyotishman Pathak

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

A(DP)²SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy.

Jie Xu, Wei Zhang, Fei Wang

CoRR, 2020

Order-Preserving Metric Learning for Mining Multivariate Time Series.

Jie Xu, Zhenxing Xu, Bin Yu, Fei Wang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Identification of Alzheimer's Disease Subtypes from Electronic Health Records Using a Data-Driven Approach.

Jie Xu, Fei Wang, Zhenxing Xu, Prakash Adekkanattu, Pascal S. Brandt, Guoqian Jiang, Richard C. Kiefer, Yuan Luo, Chengsheng Mao, Jennifer A. Pacheco, Luke V. Rasmussen, Yiye Zhang, Richard Isaacson, Jyotishman Pathak

Proceedings of the AMIA 2020, 2020

Feasibility of Cross-Platform EHR-Driven Phenotyping Using Clinical Quality Language.

Pascal S. Brandt, Richard C. Kiefer, Jennifer A. Pacheco, Prakash Adekkanattu, Evan Sholle, Faraz S. Ahmad, Jie Xu, Zhenxing Xu, Jessica S. Ancker, Fei Wang, Yuan Luo, Guoqian Jiang, Jyotishman Pathak, Luke V. Rasmussen

Proceedings of the AMIA 2020, 2020

Federated Patient Hashing.

Jie Xu, Zhenxing Xu, Peter B. Walker, Fei Wang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Federated Learning for Healthcare Informatics.

Jie Xu, Fei Wang

CoRR, 2019

Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees.

Lei Luo, Jie Xu, Cheng Deng, Heng Huang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Orthogonality-Promoting Dictionary Learning via Bayesian Inference.

Lei Luo, Jie Xu, Cheng Deng, Heng Huang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Compressed multi-scale feature fusion network for single image super-resolution.

Xinxia Fan, Yanhua Yang, Cheng Deng, Jie Xu, Xinbo Gao

Signal Process., 2018

Bilevel Distance Metric Learning for Robust Image Recognition.

Jie Xu, Lei Luo, Cheng Deng, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

New Robust Metric Learning Model Using Maximum Correntropy Criterion.

Jie Xu, Lei Luo, Cheng Deng, Heng Huang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Multi-Level Metric Learning via Smoothed Wasserstein Distance.

Jie Xu, Lei Luo, Cheng Deng, Heng Huang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Multi-Class Support Vector Machine via Maximizing Multi-Class Margins.

Jie Xu, Xianglong Liu, Zhouyuan Huo, Cheng Deng, Feiping Nie, Heng Huang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Predicting Alzheimer's Disease Cognitive Assessment via Robust Low-Rank Structured Sparse Model.

Jie Xu, Cheng Deng, Xinbo Gao, Dinggang Shen, Heng Huang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Similarity Constraints-Based Structured Output Regression Machine: An Approach to Image Super-Resolution.

Cheng Deng, Jie Xu, Kaibing Zhang, Dacheng Tao, Xinbo Gao, Xuelong Li

IEEE Trans. Neural Networks Learn. Syst., 2016

2015

Coupled fisher discrimination dictionary learning for single image super-resolution.

Songhang Ye, Cheng Deng, Jie Xu, Xinbo Gao

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014

Image Super-resolution Based on Sparse Representation With Joint Constraints.

Jie Xu, Cheng Deng, Xianglong Liu, Jie Li

Proceedings of the International Conference on Internet Multimedia Computing and Service, 2014

Image super-resolution using multi-layer support vector regression.

Jie Xu, Cheng Deng, Xinbo Gao, Dacheng Tao, Xuelong Li

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Image super resolution using Gaussian Process Regression with patch clustering.

Fang Xie, Cheng Deng, Jie Xu, Jifei Yu, Jie Li

Proceedings of the International Conference on Internet Multimedia Computing and Service, 2013