678 citations · 2.7k across the 61 of their papers we have counts for
39 papers · 1 filter
TREEMENT: Interpretable Patient-Trial Matching via Personalized Dynamic Tree-Based Memory Network
Brandon Theodorou, Cao Xiao, Jimeng Sun
Clinical trials are critical for drug development but often suffer from expensive and inefficient patient recruitment. In recent years, machine learning models have been proposed f…
Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations
Pengcheng Jiang, Cao Xiao, Tianfan Fu +4
Molecular representation learning is vital for various downstream applications, including the analysis and prediction of molecular properties and side effects. While Graph Neural N…
MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement
Zifeng Wang, Chufan Gao, Cao Xiao +1
Tabular data prediction has been employed in medical applications such as patient health risk prediction. However, existing methods usually revolve around the algorithm design whil…
SPOT: Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning
Zifeng Wang, Cao Xiao, Jimeng Sun
Clinical trials are essential to drug development but time-consuming, costly, and prone to failure. Accurate trial outcome prediction based on historical trial data promises better…
Clinical trial site matching with improved diversity using fair policy learning
Rakshith S Srinivasa, Cheng Qian, Brandon Theodorou +4
The ongoing pandemic has highlighted the importance of reliable and efficient clinical trials in healthcare. Trial sites, where the trials are conducted, are chosen mainly based on…
MedAttacker: Exploring Black-Box Adversarial Attacks on Risk Prediction Models in Healthcare
Muchao Ye, Junyu Luo, Guanjie Zheng +3
Deep neural networks (DNNs) have been broadly adopted in health risk prediction to provide healthcare diagnoses and treatments. To evaluate their robustness, existing research cond…
Differentiable Scaffolding Tree for Molecular Optimization
Tianfan Fu, Wenhao Gao, Cao Xiao +3
The structural design of functional molecules, also called molecular optimization, is an essential chemical science and engineering task with important applications, such as drug d…
Multi-version Tensor Completion for Time-delayed Spatio-temporal Data
Cheng Qian, Nikos Kargas, Cao Xiao +3
Real-world spatio-temporal data is often incomplete or inaccurate due to various data loading delays. For example, a location-disease-time tensor of case counts can have multiple d…
Change Matters: Medication Change Prediction with Recurrent Residual Networks
Chaoqi Yang, Cao Xiao, Lucas Glass +1
Deep learning is revolutionizing predictive healthcare, including recommending medications to patients with complex health conditions. Existing approaches focus on predicting all m…
Machine Learning Applications for Therapeutic Tasks with Genomics Data
Kexin Huang, Cao Xiao, Lucas M. Glass +3
Thanks to the increasing availability of genomics and other biomedical data, many machine learning approaches have been proposed for a wide range of therapeutic discovery and devel…
SafeDrug: Dual Molecular Graph Encoders for Recommending Effective and Safe Drug Combinations
Chaoqi Yang, Cao Xiao, Fenglong Ma +2
Medication recommendation is an essential task of AI for healthcare. Existing works focused on recommending drug combinations for patients with complex health conditions solely bas…
SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models
Zhen Lin, Cao Xiao, Lucas Glass +2
Despite deep learning (DL) success in classification problems, DL classifiers do not provide a sound mechanism to decide when to refrain from predicting. Recent works tried to cont…
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Kexin Huang, Tianfan Fu, Wenhao Gao +7
Therapeutics machine learning is an emerging field with incredible opportunities for innovatiaon and impact. However, advancement in this field requires formulation of meaningful l…
PyHealth: A Python Library for Health Predictive Models
Yue Zhao, Zhi Qiao, Cao Xiao +2
Despite the explosion of interest in healthcare AI research, the reproducibility and benchmarking of those research works are often limited due to the lack of standard benchmark da…
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos +3
Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures. In this work, we develop a tensor method to…
DeepRite: Deep Recurrent Inverse TreatmEnt Weighting for Adjusting Time-varying Confounding in Modern Longitudinal Observational Data
Yanbo Xu, Cao Xiao, Jimeng Sun
Counterfactual prediction is about predicting outcome of the unobserved situation from the data. For example, given patient is on drug A, what would be the outcome if she switch to…
UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data
Chacha Chen, Junjie Liang, Fenglong Ma +3
Successful health risk prediction demands accuracy and reliability of the model. Existing predictive models mainly depend on mining electronic health records (EHR) with advanced de…
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization
Tianfan Fu, Cao Xiao, Xinhao Li +2
Molecule optimization is a fundamental task for accelerating drug discovery, with the goal of generating new valid molecules that maximize multiple drug properties while maintainin…
SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization
Yue Yu, Kexin Huang, Chao Zhang +3
Thanks to the increasing availability of drug-drug interactions (DDI) datasets and large biomedical knowledge graphs (KGs), accurate detection of adverse DDI using machine learning…
COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching
Junyi Gao, Cao Xiao, Lucas M. Glass +1
Clinical trials play important roles in drug development but often suffer from expensive, inaccurate and insufficient patient recruitment. The availability of massive electronic he…
Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification
Rakshith S Srinivasa, Cao Xiao, Lucas Glass +2
The attention mechanism has demonstrated superior performance for inference over nodes in graph neural networks (GNNs), however, they result in a high computational burden during b…
CHEER: Rich Model Helps Poor Model via Knowledge Infusion
Cao Xiao, Trong Nghia Hoang, Shenda Hong +2
There is a growing interest in applying deep learning (DL) to healthcare, driven by the availability of data with multiple feature channels in rich-data environments (e.g., intensi…
DeepPurpose: a Deep Learning Library for Drug-Target Interaction Prediction
Kexin Huang, Tianfan Fu, Lucas Glass +3
Accurate prediction of drug-target interactions (DTI) is crucial for drug discovery. Recently, deep learning (DL) models for show promising performance for DTI prediction. However,…
CLARA: Clinical Report Auto-completion
Siddharth Biswal, Cao Xiao, Lucas M. Glass +2
Generating clinical reports from raw recordings such as X-rays and electroencephalogram (EEG) is an essential and routine task for doctors. However, it is often time-consuming to w…