World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
37
Citations
4932
World Ranking
2534
National Ranking
133

Research.com Recognitions

  • 2013 - Fellow of the American Statistical Association (ASA)

Overview

Guosheng Yin is affiliated with the University of Hong Kong in China. Their research spans multiple fields, primarily focusing on Mathematics and Computer Science, with notable work in subfields such as Statistics and Probability, Artificial Intelligence, Infectious Diseases, Molecular Biology, and Management Science and Operations Research.

The scientist's academic output is concentrated on several main topics, including Statistical Methods in Clinical Trials, Statistical Methods and Inference, SARS-CoV-2 and COVID-19 Research, Statistical Methods and Bayesian Inference, Optimal Experimental Design Methods, Advanced Causal Inference Techniques, and COVID-19 Clinical Research Studies.

Among their recent publications are the following papers:

  • "Reinforcement Learning in Healthcare: A Survey," 2021, ACM Computing Surveys
  • "The global, regional, and national burden of cancer among adolescents and young adults in 204 countries and territories, 1990-2019: a population-based study," 2021, Journal of Hematology & Oncology
  • "Prevention of Covid-19 with the BNT162b2 and mRNA-1273 Vaccines," 2021, New England Journal of Medicine
  • "Efficacy of COVID-19 Treatments: A Bayesian Network Meta-Analysis of Randomized Controlled Trials," 2021, Frontiers in Public Health
  • "Multiethnic polygenic risk prediction in diverse populations through transfer learning," 2022, Frontiers in Genetics

Frequent collaborators in research include Huaqing Jin, Tsai Hor Chan, Lequan Yu, Jiaqi Gu, and Yan Zhang.

Guosheng Yin publishes regularly in venues such as arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), Statistics in Medicine, Statistical Methods in Medical Research, and UNC Libraries.

In recognition of contributions to the field, Guosheng Yin was named a Fellow of the American Statistical Association (ASA) in 2013.

Best Publications

  • Cure rate models: A unified approach

    Guosheng Yin;Joseph G. Ibrahim

  • Bayesian dose finding in oncology for drug combinations by copula regression

    Guosheng Yin;Ying Yuan

  • Bayesian Model Averaging Continual Reassessment Method in Phase I Clinical Trials

    Guosheng Yin;Ying Yuan

  • Bayesian dose-finding in phase I/II clinical trials using toxicity and efficacy odds ratios

    Guosheng Yin;Yisheng Li;Yuan Ji

  • Semiparametric Transformation Models for Survival Data With a Cure Fraction

    Donglin Zeng;Guosheng Yin;Joseph G Ibrahim

  • Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

    Ying Yuan;Guosheng Yin

  • Clinical Trial Design: Bayesian and Frequentist Adaptive Methods

    Guosheng Yin

  • Nonparametric maximum likelihood approach to multiple change-point problems

    Changliang Zou;Guosheng Yin;Long Feng;Zhaojun Wang

  • A Latent Contingency Table Approach to Dose Finding for Combinations of Two Agents

    Guosheng Yin;Ying Yuan

  • Bayesian dose finding by jointly modelling toxicity and efficacy as time-to-event outcomes

    Ying Yuan;Guosheng Yin

  • Phase 3 study comparing the use of docetaxel on an every-3-week versus weekly schedule in the treatment of metastatic breast cancer†

    Edgardo Rivera;Jaime A. Mejia;Banu K. Arun;Rosnie B. Adinin

  • Bayesian optimal interval design for dose finding in drug-combination trials:

    Ruitao Lin;Guosheng Yin

  • Bayesian data augmentation dose finding with continual reassessment method and delayed toxicity

    Suyu Liu;Guosheng Yin;Ying Yuan

  • Outlier detection for high-dimensional data

    Kwangil Ro;Changliang Zou;Zhaojun Wang;Guosheng Yin

  • Conditional quantile screening in ultrahigh-dimensional heterogeneous data

    Yuanshan Wu;Guosheng Yin

  • Sequential continual reassessment method for two‐dimensional dose finding

    Ying Yuan;Guosheng Yin

  • Phase II trial design with Bayesian adaptive randomization and predictive probability

    Guosheng Yin;Nan Chen;J. Jack Lee

  • Bayesian generalized method of moments

    Guosheng Yin

  • Additive hazards model with multivariate failure time data

    Guosheng Yin;Jianwen Cai

  • Robust EM Continual Reassessment Method in Oncology Dose Finding

    Ying Yuan;Guosheng Yin

  • Using the Restricted Mean Survival Time Difference as an Alternative to the Hazard Ratio for Analyzing Clinical Cardiovascular Studies.

    Zachary R. McCaw;Guosheng Yin;Lee-Jen Wei

  • Worth Adapting? Revisiting the Usefulness of Outcome-Adaptive Randomization

    J. Jack Lee;Nan Chen;Guosheng Yin;Guosheng Yin

Frequent Co-Authors

Ying Yuan
Ying Yuan The University of Texas MD Anderson Cancer Center
Joseph G. Ibrahim
Joseph G. Ibrahim University of North Carolina at Chapel Hill
Banu Arun
Banu Arun The University of Texas MD Anderson Cancer Center
Ignacio I. Wistuba
Ignacio I. Wistuba The University of Texas MD Anderson Cancer Center
Gabriel N. Hortobagyi
Gabriel N. Hortobagyi The University of Texas MD Anderson Cancer Center
Nour Sneige
Nour Sneige The University of Texas MD Anderson Cancer Center
Waun Ki Hong
Waun Ki Hong The University of Texas MD Anderson Cancer Center
Carmen Behrens
Carmen Behrens The University of Texas MD Anderson Cancer Center
Vicente Valero
Vicente Valero The University of Texas MD Anderson Cancer Center
J. Jack Lee
J. Jack Lee The University of Texas MD Anderson Cancer Center

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