382 citations · 563 across the 24 of their papers we have counts for
25 papers
Deep Reinforcement Learning for Efficient and Fair Allocation of Health Care Resources
Yikuan Li, Chengsheng Mao, Kaixuan Huang +4
Scarcity of health care resources could result in the unavoidable consequence of rationing. For example, ventilators are often limited in supply, especially during public health em…
Exploring Large Language Models for Knowledge Graph Completion
Liang Yao, Jiazhen Peng, Chengsheng Mao +1
Knowledge graphs play a vital role in numerous artificial intelligence tasks, yet they frequently face the issue of incompleteness. In this study, we explore utilizing Large Langua…
AD-BERT: Using Pre-trained contextualized embeddings to Predict the Progression from Mild Cognitive Impairment to Alzheimer's Disease
Chengsheng Mao, Jie Xu, Luke Rasmussen +9
Objective: We develop a deep learning framework based on the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model using unstructured clinical notes from…
AKI-BERT: a Pre-trained Clinical Language Model for Early Prediction of Acute Kidney Injury
Chengsheng Mao, Liang Yao, Yuan Luo
Acute kidney injury (AKI) is a common clinical syndrome characterized by a sudden episode of kidney failure or kidney damage within a few hours or a few days. Accurate early predic…
Distribution Preserving Graph Representation Learning
Chengsheng Mao, Yuan Luo
Graph neural network (GNN) is effective to model graphs for distributed representations of nodes and an entire graph. Recently, research on the expressive power of GNN attracted gr…
Constrained tensor factorization for computational phenotyping and mortality prediction in patients with cancer
Francisco Y Cai, Chengsheng Mao, Yuan Luo
Background: The increasing adoption of electronic health records (EHR) across the US has created troves of computable data, to which machine learning methods have been applied to e…
Natural language processing to identify lupus nephritis phenotype in electronic health records
Yu Deng, Jennifer A. Pacheco, Anh Chung +14
Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one…
PANTHER: Pathway Augmented Nonnegative Tensor factorization for HighER-order feature learning
Yuan Luo, Chengsheng Mao
Genetic pathways usually encode molecular mechanisms that can inform targeted interventions. It is often challenging for existing machine learning approaches to jointly model genet…
Towards Expressive Graph Representation
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. However, most exist…
KG-BERT: BERT for Knowledge Graph Completion
Liang Yao, Chengsheng Mao, Yuan Luo
Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness. In this work, we propose to use pre-trained language models fo…
MedGCN: Medication recommendation and lab test imputation via graph convolutional networks
Chengsheng Mao, Liang Yao, Yuan Luo
Laboratory testing and medication prescription are two of the most important routines in daily clinical practice. Developing an artificial intelligence system that can automaticall…
ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification with Chest X-rays
Chengsheng Mao, Liang Yao, Yuan Luo
Image representation is a fundamental task in computer vision. However, most of the existing approaches for image representation ignore the relations between images and consider ea…
Local Probabilistic Model for Bayesian Classification: a Generalized Local Classification Model
Chengsheng Mao, Lijuan Lu, Bin Hu
In Bayesian classification, it is important to establish a probabilistic model for each class for likelihood estimation. Most of the previous methods modeled the probability distri…
Local Distribution in Neighborhood for Classification
Chengsheng Mao, Bin Hu, Lei Chen +2
The k-nearest-neighbor method performs classification tasks for a query sample based on the information contained in its neighborhood. Previous studies into the k-nearest-neighbor…
Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes
Yikuan Li, Liang Yao, Chengsheng Mao +3
Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and mortality. Development of novel methods to identify patients with AKI earlier will…
Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk
Guoqing Chao, Chengsheng Mao, Fei Wang +2
ICU mortality risk prediction is a tough yet important task. On one hand, due to the complex temporal data collected, it is difficult to identify the effective features and interpr…
Cancer classification and pathway discovery using non-negative matrix factorization
Zexian Zeng, Andy Vo, Chengsheng Mao +3
Extracting genetic information from a full range of sequencing data is important for understanding diseases. We propose a novel method to effectively explore the landscape of genet…
Distribution Networks for Open Set Learning
Chengsheng Mao, Liang Yao, Yuan Luo
In open set learning, a model must be able to generalize to novel classes when it encounters a sample that does not belong to any of the classes it has seen before. Open set learni…
Deep Generative Classifiers for Thoracic Disease Diagnosis with Chest X-ray Images
Chengsheng Mao, Yiheng Pan, Zexian Zeng +2
Thoracic diseases are very serious health problems that plague a large number of people. Chest X-ray is currently one of the most popular methods to diagnose thoracic diseases, pla…
Graph Convolutional Networks for Text Classification
Liang Yao, Chengsheng Mao, Yuan Luo
Text classification is an important and classical problem in natural language processing. There have been a number of studies that applied convolutional neural networks (convolutio…
Clinical Text Classification with Rule-based Features and Knowledge-guided Convolutional Neural Networks
Liang Yao, Chengsheng Mao, Yuan Luo
Clinical text classification is an important problem in medical natural language processing. Existing studies have conventionally focused on rules or knowledge sources-based featur…
Developing a Portable Natural Language Processing Based Phenotyping System
Himanshu Sharma, Chengsheng Mao, Yizhen Zhang +7
This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches. Our system utilizes UMLS to extr…
Are My EHRs Private Enough? -Event-level Privacy Protection
Chengsheng Mao, Yuan Zhao, Mengxin Sun +1
Privacy is a major concern in sharing human subject data to researchers for secondary analyses. A simple binary consent (opt-in or not) may significantly reduce the amount of shara…
Efficient Genomic Interval Queries Using Augmented Range Trees
Chengsheng Mao, Alal Eran, Yuan Luo
Efficient large-scale annotation of genomic intervals is essential for personal genome interpretation in the realm of precision medicine. There are 13 possible relations between tw…