678 citations · 2.7k across the 61 of their papers we have counts for
61 papers
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…
PyTrial: Machine Learning Software and Benchmark for Clinical Trial Applications
Zifeng Wang, Brandon Theodorou, Tianfan Fu +2
Clinical trials are conducted to test the effectiveness and safety of potential drugs in humans for regulatory approval. Machine learning (ML) has recently emerged as a new tool to…
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…
FRAMM: Fair Ranking with Missing Modalities for Clinical Trial Site Selection
Brandon Theodorou, Lucas Glass, Cao Xiao +1
Despite many efforts to address the disparities, the underrepresentation of gender, racial, and ethnic minorities in clinical trials remains a problem and undermines the efficacy o…
GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs
Pengcheng Jiang, Cao Xiao, Adam Cross +1
Clinical predictive models often rely on patients' electronic health records (EHR), but integrating medical knowledge to enhance predictions and decision-making is challenging. Thi…
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…
AutoTrial: Prompting Language Models for Clinical Trial Design
Zifeng Wang, Cao Xiao, Jimeng Sun
Clinical trials are critical for drug development. Constructing the appropriate eligibility criteria (i.e., the inclusion/exclusion criteria for patient recruitment) is essential f…
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…
AutoMap: Automatic Medical Code Mapping for Clinical Prediction Model Deployment
Zhenbang Wu, Cao Xiao, Lucas M Glass +2
Given a deep learning model trained on data from a source site, how to deploy the model to a target hospital automatically? How to accommodate heterogeneous medical coding systems…
PopNet: Real-Time Population-Level Disease Prediction with Data Latency
Junyi Gao, Cao Xiao, Lucas M. Glass +1
Population-level disease prediction estimates the number of potential patients of particular diseases in some location at a future time based on (frequently updated) historical dis…
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…
Self-supervised EEG Representation Learning for Automatic Sleep Staging
Chaoqi Yang, Danica Xiao, M. Brandon Westover +1
Background: Deep learning models have shown great success in automating tasks in sleep medicine by learning from carefully annotated Electroencephalogram (EEG) data. However, effec…
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…
MTC: Multiresolution Tensor Completion from Partial and Coarse Observations
Chaoqi Yang, Navjot Singh, Cao Xiao +3
Existing tensor completion formulation mostly relies on partial observations from a single tensor. However, tensors extracted from real-world data are often more complex due to: (i…
ATD: Augmenting CP Tensor Decomposition by Self Supervision
Chaoqi Yang, Cheng Qian, Navjot Singh +4
Tensor decompositions are powerful tools for dimensionality reduction and feature interpretation of multidimensional data such as signals. Existing tensor decomposition objectives…
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…
HINT: Hierarchical Interaction Network for Trial Outcome Prediction Leveraging Web Data
Tianfan Fu, Kexin Huang, Cao Xiao +2
Clinical trials are crucial for drug development but are time consuming, expensive, and often burdensome on patients. More importantly, clinical trials face uncertain outcomes due…
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…