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HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data
Clinical trials are crucial for drug development but are time consuming,...
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EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders
Researchers require timely access to real-world longitudinal electronic ...
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STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Accurate prediction of the transmission of epidemic diseases such as COV...
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FLANNEL: Focal Loss Based Neural Network Ensemble for COVID-19 Detection
To test the possibility of differentiating chest x-ray images of COVID-1...
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DeepRite: Deep Recurrent Inverse TreatmEnt Weighting for Adjusting Time-varying Confounding in Modern Longitudinal Observational Data
Counterfactual prediction is about predicting outcome of the unobserved ...
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UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data
Successful health risk prediction demands accuracy and reliability of th...
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SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
Existing tensor factorization methods assume that the input tensor follo...
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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...
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MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization
Molecule optimization is a fundamental task for accelerating drug discov...
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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...
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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...
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SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
Uncertainty quantification is a fundamental yet unsolved problem for dee...
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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...
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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...
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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...
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Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
The attention mechanism has demonstrated superior performance for infere...
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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...
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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...
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SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks
Molecular interaction networks are powerful resources for the discovery....
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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...
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DeepPurpose: a Deep Learning Based Drug Repurposing Toolkit
We present DeepPurpose, a deep learning toolkit for simple and efficient...
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CLARA: Clinical Report Auto-completion
Generating clinical reports from raw recordings such as X-rays and elect...
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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...
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StageNet: Stage-Aware Neural Networks for Health Risk Prediction
Deep learning has demonstrated success in health risk prediction especia...
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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...
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DeepEnroll: Patient-Trial Matching with Deep Embeddingand Entailment Prediction
Clinical trials are essential for drug development but often suffer from...
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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...
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CONAN: Complementary Pattern Augmentation for Rare Disease Detection
Rare diseases affect hundreds of millions of people worldwide but are ha...
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Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment
Massive electronic health records (EHRs) enable the success of learning ...
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CUP: Cluster Pruning for Compressing Deep Neural Networks
We propose Cluster Pruning (CUP) for compressing and accelerating deep n...
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CASTER: Predicting Drug Interactions with Chemical Substructure Representation
Adverse drug-drug interactions (DDIs) remain a leading cause of morbidit...
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TASTE: Temporal and Static Tensor Factorization for Phenotyping Electronic Health Records
Phenotyping electronic health records (EHR) focuses on defining meaningf...
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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...
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GENN: Predicting Correlated Drug-drug Interactions with Graph Energy Neural Networks
Gaining more comprehensive knowledge about drug-drug interactions (DDIs)...
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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...
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Rare Disease Detection by Sequence Modeling with Generative Adversarial Networks
Rare diseases affecting 350 million individuals are commonly associated ...
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Clinical Concept Extraction for Document-Level Coding
The text of clinical notes can be a valuable source of patient informati...
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Pre-training of Graph Augmented Transformers for Medication Recommendation
Medication recommendation is an important healthcare application. It is ...
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MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals
Electrocardiography (ECG) signals are commonly used to diagnose various ...
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CarePre: An Intelligent Clinical Decision Assistance System
Clinical decision support systems (CDSS) are widely used to assist with ...
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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...
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AWE: Asymmetric Word Embedding for Textual Entailment
Textual entailment is a fundamental task in natural language processing....
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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...
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GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination
Recent progress in deep learning is revolutionizing the healthcare domai...
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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...
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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...
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HAMLET: Interpretable Human And Machine co-LEarning Technique
Efficient label acquisition processes are key to obtaining robust classi...
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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...
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COPA: Constrained PARAFAC2 for Sparse & Large Datasets
PARAFAC2 has demonstrated success in modeling irregular tensors, where t...
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Explainable Prediction of Medical Codes from Clinical Text
Clinical notes are text documents that are created by clinicians for eac...
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