Yi Zhou

Assistant Professor

Kobe University

Japan

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About

Yi Zhou is an Assistant Professor at Kobe University, Japan. His research areas include meta-analysis, treatment effect visualization, self-medication practices, and cancer classification methodologies. He has recently published articles focusing on the effectiveness of psychotherapies, publication bias, and the use of interactive applications for statistical analysis.

Articles (10)

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

Collaborators (5)

Ao Huang

University Medical Center Göttingen

GERMANY

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Tatsuya TAKAGI

Specially Appointed Professor, Professor Emeritus

Osaka University

JAPAN

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Noriyasu Hashida

Associate Professor

Osaka University

JAPAN

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Yu-Shi Tian

Osaka University

JAPAN

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Satoshi Hattori

Osaka University

JAPAN

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Yi Zhou

Research Interests

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About

Articles (10)

CSTEapp: An interactive R-Shiny application of the covariate-specific treatment effect curve for visualizing individualized treatment rule

Status and influencing factors of OTC medicine use for self-medication in cold and cough: a cross-sectional survey in Japan

Sensitivity analysis for reporting bias on the time-dependent summary receiver operating characteristics curve in meta-analysis of prognosis studies with time-to-event outcomes

A Simple Sensitivity Analysis Method for Unmeasured Confounders via Linear Programming With Estimating Equation Constraints

Nonparametric worst-case bounds for publication bias on the summary receiver operating characteristic curve

Sensitivity analysis for publication bias in meta-analysis of sparse data based on exact likelihood

Network meta-analysis of the effectiveness of psychotherapies with or without medication for treating adult depression

The Efficacy of Golimumab Against Non-Infectious Uveitis: A PRISMA-Compliant Systematic Review and Meta-Analysis

DTAmetasa: An R shiny application for meta-analysis of diagnostic test accuracy and sensitivity analysis of publication bias

Genetic algorithm-based feature selection with manifold learning for cancer classification using microarray data

Collaborators (5)

Ao Huang

Tatsuya TAKAGI

Noriyasu Hashida

Yu-Shi Tian

Satoshi Hattori

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