78 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Yale UniversityUS15 papers
- Harvard UniversityUS4 papers
- Rutgers, The State University of New JerseyUS3 papers
- Yale New Haven HospitalUS3 papers
- Cancer Research And BiostatisticsUS2 papers
- Imperial College LondonGB2 papers
- University of California San DiegoUS2 papers
- All India Institute of Medical SciencesIN1 paper
- Amsterdam UMC Location Vrije Universiteit AmsterdamNL1 paper
- Arizona State UniversityUS1 paper
- Brigham and Women's HospitalUS1 paper
- Chinese Academy of Medical Sciences & Peking Union Medical CollegeCN1 paper
21 papers
Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications
Anran Li, Lingfei Qian, Mengmeng Du +18
Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-training or fine-tuning on medical data to e…
Improving Transportability of Regression Calibration Under the Main/External Validation Study Design
Zexiang Li, Donna Spiegelman, Molin Wang +2
In epidemiology, obtaining accurate individual exposure measurements can be costly and challenging. Thus, these measurements are often subject to error. Regression calibration with…
A tutorial on conducting sample size and power calculations for detecting treatment effect heterogeneity in cluster randomized trials with linear mixed models
Mary Ryan Baumann, Monica Taljaard, Patrick J. Heagerty +4
Cluster-randomized trials (CRTs) are a well-established class of designs for evaluating community-based interventions. An essential task in planning these trials is determining the…
A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding
Xinyuan Chen, Liangyuan Hu, Fan Li
In longitudinal observational studies with time-to-event outcomes, a common objective in causal analysis is to estimate the causal survival curve under hypothetical intervention sc…
Maximin optimal cluster randomized designs for assessing treatment effect heterogeneity
Mary M. Ryan, Denise Esserman, Fan Li
Cluster randomized trials (CRTs) are studies where treatment is randomized at the cluster level but outcomes are typically collected at the individual level. When CRTs are employed…
Causal Selection of Covariates in Regression Calibration for Mismeasured Continuous Exposure
Wenze Tang, Donna Spiegelman, Xiaomei Liao +1
Regression calibration as developed by Rosner, Spiegelman and Willet is used to correct the bias in effect estimates due to measurement error in continuous exposures. The method in…
Self-supervised contrastive learning of echocardiogram videos enables label-efficient cardiac disease diagnosis
Gregory Holste, Evangelos K. Oikonomou, Bobak J. Mortazavi +2
Advances in self-supervised learning (SSL) have shown that self-supervised pretraining on medical imaging data can provide a strong initialization for downstream supervised classif…
Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid
Irina Degtiar, Tim Layton, Jacob Wallace +1
While much of the causal inference literature has focused on addressing internal validity biases, both internal and external validity are necessary for unbiased estimates in a targ…
Generalizing trial evidence to target populations in non-nested designs: Applications to AIDS clinical trials
Fan Li, Ashley L. Buchanan, Stephen R. Cole
Comparative effectiveness evidence from randomized trials may not be directly generalizable to a target population of substantive interest when, as in most cases, trial participant…
Estimating heterogeneous survival treatment effect in observational data using machine learning
Liangyuan Hu, Jiayi Ji, Fan Li
Methods for estimating heterogeneous treatment effect in observational data have largely focused on continuous or binary outcomes, and have been relatively less vetted with surviva…
Multi-way Graph Signal Processing on Tensors: Integrative analysis of irregular geometries
Jay S. Stanley, Eric C. Chi, Gal Mishne
Graph signal processing (GSP) is an important methodology for studying data residing on irregular structures. As acquired data is increasingly taking the form of multi-way tensors,…
A Scalable Data Science Platform for Healthcare and Precision Medicine Research
Jacob McPadden, Thomas JS Durant, Dustin R Bunch +9
Objective: To (1) demonstrate the implementation of a data science platform built on open-source technology within a large, academic healthcare system and (2) describe two computat…
TrialChain: A Blockchain-Based Platform to Validate Data Integrity in Large, Biomedical Research Studies
Hao Dai, H Patrick Young, Thomas JS Durant +5
The governance of data used for biomedical research and clinical trials is an important requirement for generating accurate results. To improve the visibility of data quality and a…
A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis
Salman Razzaki, Adam Baker, Yura Perov +10
Online symptom checkers have significant potential to improve patient care, however their reliability and accuracy remain variable. We hypothesised that an artificial intelligence…
Kinetics of Protein-DNA Interactions: First-Passage Analysis
Maria P. Kochugaeva, Alexey A. Shvets, Anatoly B. Kolomeisky
All living systems can function only far away from equilibrium, and for this reason chemical kinetic methods are critically important for uncovering the mechanisms of biological pr…
Risk Factors Associated with Mortality in Game of Thrones: A Longitudinal Cohort Study
Suveen Angraal, Ambika Bhatnagar, Suraj Verma +3
Objective: To assess mortality, and identify the risk factors associated with mortality in Game of Thrones (GoT). Design and Setting: A longitudinal cohort study in the fictional k…
On Consistency of Graph-based Semi-supervised Learning
Chengan Du, Yunpeng Zhao, Feng Wang
Graph-based semi-supervised learning is one of the most popular methods in machine learning. Some of its theoretical properties such as bounds for the generalization error and the…
Pathophysiological Domains Underlying the Metabolic Syndrome: An Alternative Factor Analytic Strategy
Carel F. W. Peeters, James Dziura, Floryt van Wesel
Purpose: Factor analysis (FA) has become part and parcel in metabolic syndrome (MBS) research. Both exploration- and confirmation-driven factor analyzes are rampant. However, facto…
A Stopped Negative Binomial Distribution
Michelle DeVeaux, Michael J. Kane, Daniel Zelterman
This paper introduces a new discrete distribution suggested by curtailed sampling rules common in early-stage clinical trials. We derive the distribution of the smallest number of…
On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data
Zhixiang Lin, Tao Wang, Can Yang +1
In this paper, we first propose a Bayesian neighborhood selection method to estimate Gaussian Graphical Models (GGMs). We show the graph selection consistency of this method in the…
Semi-Penalized Inference with Direct False Discovery Rate Control in High-Dimensions
Jian Huang, Shuangge Ma, Cun-Hui Zhang +1
We propose a new method, semi-penalized inference with direct false discovery rate control (SPIDR), for variable selection and confidence interval construction in high-dimensional…