Search Results for author: Yuan Luo

Found 39 papers, 12 papers with code

Development and Validation of MicrobEx: an Open-Source Package for Microbiology Culture Concept Extraction

no code implementations22 Nov 2021 Garrett Eickelberg, Yuan Luo, L. Nelson Sanchez-Pinto

Our concept extraction Python package, MicrobEx, is designed to be reused and adapted to individual institutions as an upstream process for other clinical applications, such as machine learning studies, clinical decision support, and disease surveillance systems.

Assessing Social Determinants-Related Performance Bias of Machine Learning Models: A case of Hyperchloremia Prediction in ICU Population

no code implementations18 Nov 2021 Songzi Liu, Yuan Luo

Machine learning in medicine leverages the wealth of healthcare data to extract knowledge, facilitate clinical decision-making, and ultimately improve care delivery.

Decision Making

Unsupervised Learning to Subphenotype Delirium Patients from Electronic Health Records

no code implementations31 Oct 2021 Yiqing Zhao, Yuan Luo

Delirium is a common acute onset brain dysfunction in the emergency setting and is associated with higher mortality.

Feature Importance

Towards Understanding Catastrophic Overfitting in Fast Adversarial Training

no code implementations29 Sep 2021 Renjie Chen, Yuan Luo, Yisen Wang

After adversarial training was proposed, a series of works focus on improving the compunational efficiency of adversarial training for deep neural networks (DNNs).

Aggregation Delayed Federated Learning

1 code implementation17 Aug 2021 Ye Xue, Diego Klabjan, Yuan Luo

Federated learning is a distributed machine learning paradigm where multiple data owners (clients) collaboratively train one machine learning model while keeping data on their own devices.

Federated Learning

Non-Convex Optimization with Spectral Radius Regularization

no code implementations22 Feb 2021 Adam Sandler, Diego Klabjan, Yuan Luo

We develop a regularization method which finds flat minima during the training of deep neural networks and other machine learning models.

PANTHER: Pathway Augmented Nonnegative Tensor factorization for HighER-order feature learning

1 code implementation15 Dec 2020 Yuan Luo, Chengsheng Mao

We apply genetically motivated constrained tensor factorization to group pathways in a way that reflects molecular mechanism interactions.

Interpretable Machine Learning

Improving Medical NLI Using Context-Aware Domain Knowledge

no code implementations Joint Conference on Lexical and Computational Semantics 2020 Shaika Chowdhury, Philip Yu, Yuan Luo

Domain knowledge is important to understand both the lexical and relational associations of words in natural language text, especially for domain-specific tasks like Natural Language Inference (NLI) in the medical domain, where due to the lack of a large annotated dataset such knowledge cannot be implicitly learned during training.

Natural Language Inference

Towards Expressive Graph Representation

1 code implementation12 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.

Graph Classification Graph Representation Learning

A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports

1 code implementation3 Sep 2020 Yikuan Li, Hanyin Wang, Yuan Luo

Joint image-text embedding extracted from medical images and associated contextual reports is the bedrock for most biomedical vision-and-language (V+L) tasks, including medical visual question answering, clinical image-text retrieval, clinical report auto-generation.

Medical Visual Question Answering Question Answering +2

Decentralized Source Localization without Sensor Parameters in Wireless Sensor Networks

no code implementations2 Sep 2020 Akram Hussain, Yuan Luo

However, we propose two methods to estimate the source location in this paper under the fault model: hitting set approach and feature selection method, which only utilize the noisy data set at the fusion center for estimation of the source location without knowing the sensor parameters.

Feature Selection

Open-Set Recognition with Gaussian Mixture Variational Autoencoders

no code implementations3 Jun 2020 Alexander Cao, Yuan Luo, Diego Klabjan

In inference, open-set classification is to either classify a sample into a known class from training or reject it as an unknown class.

Classification General Classification +1

Med2Meta: Learning Representations of Medical Concepts with Meta-Embeddings

no code implementations6 Dec 2019 Shaika Chowdhury, Chenwei Zhang, Philip S. Yu, Yuan Luo

Distributed representations of medical concepts have been used to support downstream clinical tasks recently.

Decision Making

Conditional Hierarchical Bayesian Tucker Decomposition

no code implementations27 Nov 2019 Adam Sandler, Diego Klabjan, Yuan Luo

We combine this information into a tensor of patients, counts of their genetic variants, and the membership of these genes in pathways.

Tensor Decomposition

Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation

no code implementations IJCNLP 2019 Min Zeng, Yisen Wang, Yuan Luo

Based on which, we further find that there is redundancy among the dimensions of latent variable, and the lengths and sentence patterns of the responses can be strongly correlated to each dimension of the latent variable.

Dialogue Generation

Hierarchical Semantic Correspondence Learning for Post-Discharge Patient Mortality Prediction

no code implementations15 Oct 2019 Shaika Chowdhury, Chenwei Zhang, Philip S. Yu, Yuan Luo

Predicting patient mortality is an important and challenging problem in the healthcare domain, especially for intensive care unit (ICU) patients.

Mortality Prediction Semantic correspondence

KG-BERT: BERT for Knowledge Graph Completion

3 code implementations7 Sep 2019 Liang Yao, Chengsheng Mao, Yuan Luo

Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness.

Ranked #4 on Link Prediction on FB15k-237 (MR metric)

Knowledge Graph Completion Language Modelling +2

Symmetric Cross Entropy for Robust Learning with Noisy Labels

3 code implementations ICCV 2019 Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jin-Feng Yi, James Bailey

In this paper, we show that DNN learning with Cross Entropy (CE) exhibits overfitting to noisy labels on some classes ("easy" classes), but more surprisingly, it also suffers from significant under learning on some other classes ("hard" classes).

Learning with noisy labels

Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension

1 code implementation12 Aug 2019 Ye Xue, Diego Klabjan, Yuan Luo

The problem of missing values in multivariable time series is a key challenge in many applications such as clinical data mining.

Gaussian Processes Imputation +1

Identifying Sub-Phenotypes of Acute Kidney Injury using Structured and Unstructured Electronic Health Record Data with Memory Networks

no code implementations10 Apr 2019 Zhen-Xing Xu, Jingyuan Chou, Xi Sheryl Zhang, Yuan Luo, Tamara Isakova, Prakash Adekkanattu, Jessica S. Ancker, Guoqian Jiang, Richard C. Kiefer, Jennifer A. Pacheco, Luke V. Rasmussen, Jyotishman Pathak, Fei Wang

Sub-phenotype III is with average age 65. 07$ \pm 11. 32 $ years, and was characterized moderate loss of kidney excretory function and thus more likely to develop stage II AKI (SCr $1. 69\pm 0. 32$ mg/dL, eGFR $93. 97\pm 56. 53$ mL/min/1. 73$m^2$).

Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study

no code implementations2 Apr 2019 Prakash Adekkanattu, Guoqian Jiang, Yuan Luo, Paul R. Kingsbury, Zhen-Xing Xu, Luke V. Rasmussen, Jennifer A. Pacheco, Richard C. Kiefer, Daniel J. Stone, Pascal S. Brandt, Liang Yao, Yizhen Zhong, Yu Deng, Fei Wang, Jessica S. Ancker, Thomas R. Campion, Jyotishman Pathak

While the NLP system showed high precision and recall measurements for four target concepts (aortic valve regurgitation, left atrium size at end systole, mitral valve regurgitation, tricuspid valve regurgitation) across all sites, we found moderate or poor results for the remaining concepts and the NLP system performance varied between individual sites.

Medication Recommendation and Lab Test Imputation via Graph Convolutional Networks

1 code implementation31 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.

Imputation

ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification with Chest X-rays

no code implementations31 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.

Object Detection

Implementing a Portable Clinical NLP System with a Common Data Model - a Lisp Perspective

no code implementations15 Nov 2018 Yuan Luo, Peter Szolovits

We also developed a utility to convert an inline annotation format to stand-off annotations to enable the reuse of clinical text datasets with inline annotations.

Computational Phenotyping Domain Adaptation +1

Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk

no code implementations27 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.

ICU Mortality Time Series

Distribution Networks for Open Set Learning

no code implementations20 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.

Classification General Classification +1

Deep Generative Classifiers for Thoracic Disease Diagnosis with Chest X-ray Images

1 code implementation20 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.

General Classification Image Classification

Graph Convolutional Networks for Text Classification

8 code implementations15 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.

Classification General Classification +2

Developing a Portable Natural Language Processing Based Phenotyping System

1 code implementation17 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.

Natural Language Processing for EHR-Based Computational Phenotyping

no code implementations13 Jun 2018 Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann, Yuan Luo

This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping.

Computational Phenotyping

Using Clinical Narratives and Structured Data to Identify Distant Recurrences in Breast Cancer

no code implementations13 Jun 2018 Zexian Zeng, Ankita Roy, Xiaoyu Li, Sasa Espino, Susan Clare, Seema Khan, Yuan Luo

Our model can accurately and efficiently identify distant recurrences in breast cancer by combining features extracted from unstructured clinical narratives and structured clinical data.

Computational Phenotyping

Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease

1 code implementation22 May 2018 Xi Sheryl Zhang, Lifang He, Kun Chen, Yuan Luo, Jiayu Zhou, Fei Wang

Parkinson's Disease (PD) is one of the most prevalent neurodegenerative diseases that affects tens of millions of Americans.

Parametric Prediction from Parametric Agents

no code implementations24 Feb 2016 Yuan Luo, Nihar B. Shah, Jianwei Huang, Jean Walrand

In order to elicit heterogeneous agents' private information and incentivize agents with different capabilities to act in the principal's best interest, we design an optimal joint incentive mechanism and prediction algorithm called COPE (COst and Prediction Elicitation), the analysis of which offers several valuable engineering insights.

Learning Theory

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