activity
20202026
most citedText mining and sentiment analysis of COVID-19 tweets

9 citations · 16 across the 7 of their papers we have counts for

collaborators

7 papers

stat.ML2026★ 1 cited

Boosting methods for interval-censored data with regression and classification

Yuan Bian, Grace Y. Yi, Wenqing He

Boosting has garnered significant interest across both machine learning and statistical communities. Traditional boosting algorithms, designed for fully observed random samples, of…

stat.ME2025

A Flexible Partially Linear Single Index Proportional Hazards Regression Model for Multivariate Survival Data

Na Lei, Mark A. Wolters, Wenqing He

We address the problem of survival regression modelling with multivariate responses and nonlinear covariate effects. Our model extends the proportional hazards model by introducing…

stat.ME2025

Boosting prediction with data missing not at random

Yuan Bian, Grace Y. Yi, Wenqing He

Boosting has emerged as a useful machine learning technique over the past three decades, attracting increased attention. Most advancements in this area, however, have primarily foc…

stat.ME2024

Fast variational Bayesian inference for correlated survival data: an application to invasive mechanical ventilation duration analysis

Chengqian Xian, Camila P. E. de Souza, Wenqing He +2

Correlated survival data are prevalent in various clinical settings and have been extensively discussed in literature. One of the most common types of correlated survival data is c…

stat.ME2023

Variational Bayesian analysis of survival data using a log-logistic accelerated failure time model

Chengqian Xian, Camila P. E. de Souza, Wenqing He +2

The log-logistic regression model is one of the most commonly used accelerated failure time (AFT) models in survival analysis, for which statistical inference methods are mainly es…

cs.SI2021★ 9 cited

Text mining and sentiment analysis of COVID-19 tweets

Qihuang Zhang, Grace Y. Yi, Li-Pang Chen +1

The human severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), causing the COVID-19 disease, has continued to spread all over the world. It menacingly affects not only pub…

stat.AP2020★ 6 cited

COVID-19: Should We Test Everyone?

Grace Yi, Wenqing He, Dennis Kon-Jin Lin +1

Since the beginning of 2020, the coronavirus disease 2019 (COVID-19) has spread rapidly in the city of Wuhan, P.R. China, and subsequently, across the world. The swift spread of th…