678 citations · 2.6k across the 71 of their papers we have counts for
73 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…
Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models
Pengcheng Jiang, Shivam Agarwal, Bowen Jin +3
The mission of open knowledge graph (KG) completion is to draw new findings from known facts. Existing works that augment KG completion require either (1) factual triples to enlarg…
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Large language models (LLMs) specializing in natural language generation (NLG) have recently started exhibiting promising capabilities across a variety of domains. However, gauging…
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…
Reinforced Genetic Algorithm for Structure-based Drug Design
Tianfan Fu, Wenhao Gao, Connor W. Coley +1
Structure-based drug design (SBDD) aims to discover drug candidates by finding molecules (ligands) that bind tightly to a disease-related protein (targets), which is the primary ap…
Conformal Prediction with Temporal Quantile Adjustments
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
We develop Temporal Quantile Adjustment (TQA), a general method to construct efficient and valid prediction intervals (PIs) for regression on cross-sectional time series data. Such…
GOCPT: Generalized Online Canonical Polyadic Tensor Factorization and Completion
Chaoqi Yang, Cheng Qian, Jimeng Sun
Low-rank tensor factorization or completion is well-studied and applied in various online settings, such as online tensor factorization (where the temporal mode grows) and online t…
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…
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design
Yuanqi Du, Tianfan Fu, Jimeng Sun +1
Molecule design is a fundamental problem in molecular science and has critical applications in a variety of areas, such as drug discovery, material science, etc. However, due to th…
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…
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…
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
Crucial for building trust in deep learning models for critical real-world applications is efficient and theoretically sound uncertainty quantification, a task that continues to be…
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…
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…
EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders
Siddharth Biswal, Soumya Ghosh, Jon Duke +3
Researchers require timely access to real-world longitudinal electronic health records (EHR) to develop, test, validate, and implement machine learning solutions that improve the q…
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…