Jimeng Sun

UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data

Successful health risk prediction demands accuracy and reliability of th...
10/22/2020 ∙ by Chacha Chen, et al. ∙ 10 ∙ share

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SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors

Existing tensor factorization methods assume that the input tensor follo...
10/08/2020 ∙ by Ardavan Afshar, et al. ∙ 0 ∙ share

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MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning

The efficacy of a drug depends on its binding affinity to the therapeuti...
10/05/2020 ∙ by Kexin Huang, et al. ∙ 0 ∙ share

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MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization

Molecule optimization is a fundamental task for accelerating drug discov...
10/05/2020 ∙ by Tianfan Fu, et al. ∙ 13 ∙ share

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SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization

Thanks to the increasing availability of drug-drug interactions (DDI) da...
10/04/2020 ∙ by Yue Yu, et al. ∙ 0 ∙ share

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Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning

Time-series forecasting is one of the most active research topics in pre...
08/28/2020 ∙ by Gabriel Spadon, et al. ∙ 54 ∙ share

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SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates

Uncertainty quantification is a fundamental yet unsolved problem for dee...
08/24/2020 ∙ by Lingkai Kong, et al. ∙ 22 ∙ share

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HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units

Deep learning models have achieved expert-level performance in healthcar...
08/10/2020 ∙ by Shenda Hong, et al. ∙ 0 ∙ share

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EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision

Deep generative models have enabled the automated synthesis of high-qual...
07/10/2020 ∙ by Siddharth Biswal, et al. ∙ 0 ∙ share

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ELF: An Early-Exiting Framework for Long-Tailed Classification

The natural world often follows a long-tailed data distribution where on...
06/22/2020 ∙ by Rahul Duggal, et al. ∙ 7 ∙ share

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Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification

The attention mechanism has demonstrated superior performance for infere...
06/15/2020 ∙ by Rakshith S Srinivasa, et al. ∙ 0 ∙ share

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COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching

Clinical trials play important roles in drug development but often suffe...
06/15/2020 ∙ by Junyi Gao, et al. ∙ 0 ∙ share

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CHEER: Rich Model Helps Poor Model via Knowledge Infusion

There is a growing interest in applying deep learning (DL) to healthcare...
05/21/2020 ∙ by Cao Xiao, et al. ∙ 0 ∙ share

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SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks

Molecular interaction networks are powerful resources for the discovery....
04/30/2020 ∙ by Kexin Huang, et al. ∙ 0 ∙ share

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MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction

Drug target interaction (DTI) prediction is a foundational task for in s...
04/23/2020 ∙ by Kexin Huang, et al. ∙ 0 ∙ share

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DeepPurpose: a Deep Learning Based Drug Repurposing Toolkit

We present DeepPurpose, a deep learning toolkit for simple and efficient...
04/19/2020 ∙ by Kexin Huang, et al. ∙ 16 ∙ share

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CLARA: Clinical Report Auto-completion

Generating clinical reports from raw recordings such as X-rays and elect...
02/26/2020 ∙ by Siddharth Biswal, et al. ∙ 0 ∙ share

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REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild

In recent years, significant attention has been devoted towards integrat...
01/29/2020 ∙ by Rahul Duggal, et al. ∙ 116 ∙ share

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StageNet: Stage-Aware Neural Networks for Health Risk Prediction

Deep learning has demonstrated success in health risk prediction especia...
01/24/2020 ∙ by Junyi Gao, et al. ∙ 33 ∙ share

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DeepEnroll: Patient-Trial Matching with Deep Embedding and Entailment Prediction

Clinical trials are essential for drug development but often suffer from...
01/22/2020 ∙ by Xingyao Zhang, et al. ∙ 0 ∙ share

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DeepEnroll: Patient-Trial Matching with Deep Embeddingand Entailment Prediction

Clinical trials are essential for drug development but often suffer from...
01/22/2020 ∙ by Xingyao Zhang, et al. ∙ 0 ∙ share

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Opportunities and Challenges in Deep Learning Methods on Electrocardiogram Data: A Systematic Review

Objective: To conduct a systematic review of deep learning methods on El...
12/28/2019 ∙ by Shenda Hong, et al. ∙ 0 ∙ share

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CONAN: Complementary Pattern Augmentation for Rare Disease Detection

Rare diseases affect hundreds of millions of people worldwide but are ha...
11/26/2019 ∙ by Limeng Cui, et al. ∙ 0 ∙ share

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Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment

Massive electronic health records (EHRs) enable the success of learning ...
11/23/2019 ∙ by Siddharth Biswal, et al. ∙ 0 ∙ share

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CUP: Cluster Pruning for Compressing Deep Neural Networks

We propose Cluster Pruning (CUP) for compressing and accelerating deep n...
11/19/2019 ∙ by Rahul Duggal, et al. ∙ 0 ∙ share

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CASTER: Predicting Drug Interactions with Chemical Substructure Representation

Adverse drug-drug interactions (DDIs) remain a leading cause of morbidit...
11/15/2019 ∙ by Kexin Huang, et al. ∙ 0 ∙ share

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TASTE: Temporal and Static Tensor Factorization for Phenotyping Electronic Health Records

Phenotyping electronic health records (EHR) focuses on defining meaningf...
11/13/2019 ∙ by Ardavan Afshar, et al. ∙ 12 ∙ share

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SLEEPER: interpretable Sleep staging via Prototypes from Expert Rules

Sleep staging is a crucial task for diagnosing sleep disorders. It is te...
10/14/2019 ∙ by Irfan Al-Hussaini, et al. ∙ 0 ∙ share

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GENN: Predicting Correlated Drug-drug Interactions with Graph Energy Neural Networks

Gaining more comprehensive knowledge about drug-drug interactions (DDIs)...
10/04/2019 ∙ by Tengfei Ma, et al. ∙ 0 ∙ share

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Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model

Many computational models were proposed to extract temporal patterns fro...
07/01/2019 ∙ by Fan Zhang, et al. ∙ 0 ∙ share

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Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks

Rare diseases affecting 350 million individuals are commonly associated ...
07/01/2019 ∙ by Kezi Yu, et al. ∙ 0 ∙ share

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Clinical Concept Extraction for Document-Level Coding

The text of clinical notes can be a valuable source of patient informati...
06/08/2019 ∙ by Sarah Wiegreffe, et al. ∙ 0 ∙ share

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Pre-training of Graph Augmented Transformers for Medication Recommendation

Medication recommendation is an important healthcare application. It is ...
06/02/2019 ∙ by Junyuan Shang, et al. ∙ 0 ∙ share

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MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals

Electrocardiography (ECG) signals are commonly used to diagnose various ...
05/27/2019 ∙ by Shenda Hong, et al. ∙ 0 ∙ share

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CarePre: An Intelligent Clinical Decision Assistance System

Clinical decision support systems (CDSS) are widely used to assist with ...
11/06/2018 ∙ by Zhuochen Jin, et al. ∙ 0 ∙ share

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MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare

Deep learning models exhibit state-of-the-art performance for many predi...
10/22/2018 ∙ by Edward Choi, et al. ∙ 0 ∙ share

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AWE: Asymmetric Word Embedding for Textual Entailment

Textual entailment is a fundamental task in natural language processing....
09/11/2018 ∙ by Tengfei Ma, et al. ∙ 0 ∙ share

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RDPD: Rich Data Helps Poor Data via Imitation

In many situations, we have both rich- and poor- data environments: in a...
09/06/2018 ∙ by Shenda Hong, et al. ∙ 0 ∙ share

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GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

Recent progress in deep learning is revolutionizing the healthcare domai...
09/06/2018 ∙ by Junyuan Shang, et al. ∙ 0 ∙ share

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RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data

With the improvement of medical data capturing, vast amount of continuou...
07/23/2018 ∙ by Yanbo Xu, et al. ∙ 0 ∙ share

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RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records

In the past decade, we have seen many successful applications of recurre...
05/28/2018 ∙ by Bum Chul Kwon, et al. ∙ 0 ∙ share

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HAMLET: Interpretable Human And Machine co-LEarning Technique

Efficient label acquisition processes are key to obtaining robust classi...
03/26/2018 ∙ by Olivier Deiss, et al. ∙ 0 ∙ share

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SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping

This paper presents a new method, which we call SUSTain, that extends re...
03/14/2018 ∙ by Ioakeim Perros, et al. ∙ 0 ∙ share

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COPA: Constrained PARAFAC2 for Sparse & Large Datasets

PARAFAC2 has demonstrated success in modeling irregular tensors, where t...
03/12/2018 ∙ by Ardavan Afshar, et al. ∙ 0 ∙ share

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Explainable Prediction of Medical Codes from Clinical Text

Clinical notes are text documents that are created by clinicians for eac...
02/15/2018 ∙ by James Mullenbach, et al. ∙ 0 ∙ share

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Federated Tensor Factorization for Computational Phenotyping

Tensor factorization models offer an effective approach to convert massi...
04/11/2017 ∙ by Yejin Kim, et al. ∙ 0 ∙ share

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Generating Multi-label Discrete Patient Records using Generative Adversarial Networks

Access to electronic health record (EHR) data has motivated computationa...
03/19/2017 ∙ by Edward Choi, et al. ∙ 0 ∙ share

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SPARTan: Scalable PARAFAC2 for Large & Sparse Data

In exploratory tensor mining, a common problem is how to analyze a set o...
03/13/2017 ∙ by Ioakeim Perros, et al. ∙ 0 ∙ share

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Causal Regularization

In application domains such as healthcare, we want accurate predictive m...
02/08/2017 ∙ by Mohammad Taha Bahadori, et al. ∙ 0 ∙ share

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RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

Accuracy and interpretability are two dominant features of successful pr...
08/19/2016 ∙ by Edward Choi, et al. ∙ 0 ∙ share

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Jimeng Sun

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