678 citations · 1.6k across the 35 of their papers we have counts for
35 papers
TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets
Jintai Chen, Yaojun Hu, Mingchen Cai +13
Clinical trials are pivotal for developing new medical treatments but typically carry risks such as patient mortality and enrollment failure that waste immense efforts spanning ove…
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…
DeCom: Deep Coupled-Factorization Machine for Post COVID-19 Respiratory Syncytial Virus Prediction with Nonpharmaceutical Interventions Awareness
Xinyan Li, Cheng Qian, Lucas Glass
Respiratory syncytial virus (RSV) is one of the most dangerous respiratory diseases for infants and young children. Due to the nonpharmaceutical intervention (NPI) imposed in the C…
Knowledge-Driven New Drug Recommendation
Zhenbang Wu, Huaxiu Yao, Zhe Su +5
Drug recommendation assists doctors in prescribing personalized medications to patients based on their health conditions. Existing drug recommendation solutions adopt the supervise…
Artificial Intelligence for In Silico Clinical Trials: A Review
Zifeng Wang, Chufan Gao, Lucas M. Glass +1
A clinical trial is an essential step in drug development, which is often costly and time-consuming. In silico trials are clinical trials conducted digitally through simulation and…
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…
JULIA: Joint Multi-linear and Nonlinear Identification for Tensor Completion
Cheng Qian, Kejun Huang, Lucas Glass +2
Tensor completion aims at imputing missing entries from a partially observed tensor. Existing tensor completion methods often assume either multi-linear or nonlinear relationships…
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…
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…
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…
FLANNEL: Focal Loss Based Neural Network Ensemble for COVID-19 Detection
Zhi Qiao, Austin Bae, Lucas M. Glass +2
To test the possibility of differentiating chest x-ray images of COVID-19 against other pneumonia and healthy patients using deep neural networks. We construct the X-ray imaging da…
MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning
Kexin Huang, Tianfan Fu, Dawood Khan +7
The efficacy of a drug depends on its binding affinity to the therapeutic target and pharmacokinetics. Deep learning (DL) has demonstrated remarkable progress in predicting drug ef…
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…
STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real World Evidence
Junyi Gao, Rakshith Sharma, Cheng Qian +5
Objective: The COVID-19 pandemic has created many challenges that need immediate attention. Various epidemiological and deep learning models have been developed to predict the COVI…
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…