プロフィール詳細

プロジェクトを作成

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Dr. Yuan G.に依頼

United States

PhD Biostatistician | Phase 1-3 oncology trials, FDA submissions | Trial design, drug development, real-world evidence

プロフィール概要

PhD biostatistician with experience across global Phase 1 to 3 oncology development and large-scale real-world evidence. At Incyte I worked on statistical design and analysis for oncology trials in non-small cell lung cancer, squamous cell carcinoma of the anal canal, and chronic graft-versus-host disease. I defined endpoints, wrote the statistical analysis plans, and ran the analyses that supported regulatory submissions and two FDA approvals. I applied inverse-probability-of-censoring weighting to correct informative treatment crossover in survival analysis; that work contributed to a publication in The Lancet. At Stanford I authored the statistical sections of study protocols and IND submissions, ran sample size and power calculations, and wrote statistical analysis plans for investigator-initiated studies. I was lead statistician on a PCORI cluster-randomized comparative-effectiveness trial across 26 sites. In parallel I designed and ran observational studies on claims (MarketScan), EHR and registry data, using marginal structural models, inverse-probability weighting and propensity score matching to handle time-varying confounding. I am the founder of TrialCraft.io, where I build LLM and retrieval workflows over regulatory guidance and clinical-development knowledge to support protocol and endpoint planning. I have also built small-language-model pipelines that extract structured clinical variables from unstructured clinical notes as a computational alternative to manual chart review. I work in R (primary), SAS, SQL and Python. 20+ peer-reviewed publications; peer reviewer for 70+ manuscripts. PhD Biostatistics, George Washington University. MS Computer Science (AI) in progress, Georgia Tech.

専門分野

• ☆ Biostatistics
• ☆ R
• ☆ Clinical Trials
• ☆ Clinical Trial Design
• ☆ Clinical Trial Site Selection & Monitoring
• ☆ Clinical Trials Data Analysis

サービス

• Writing
• Data & AI

Writing Clinical Trial Documentation

Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Cleaning, Data Processing, Data Insights

職務経験

Stanford University

- 現在

Senior Biostatistician

Stanford University School of Medicine

12月 2023 - 9月 2026

Principal Biostatistician

Incyte Corporation

9月 2020 - 11月 2023

Data Analyst and Research Associate

University of Maryland Baltimore

5月 2019 - 5月 2020

学歴

PhD in Biostatistics

George Washington University

8月 2015 - 5月 2020

認定資格

• 認定資格の詳細は未入力です。

出版物

JOURNAL ARTICLE

Yuan Gu, Xin Li (2026). What are the most important factors for depression among HIV patients?: a study from Bangladesh . HIV & AIDS Review.

Yuan Gu, Neha S. Joshi, Jochen Profit, Adam Frymoyer, Valerie J. Flaherman, Henry C. Lee (2025). Infants Born at Late Preterm Gestation: Management during the Birth Hospitalization . The Journal of Pediatrics.

Gu, Yuan, Nissen, Silas Boye, Weiner, Alexis T, Suyama, Kaye, Bosch, PabloSanchez, Yu, Maiya, Song, Song, Dunn, Alexander R., Axelrod, Jeffrey D. (2025). Cluster Assembly Dynamics Drive Fidelity of Planar Cell Polarity Polarization . BioRxiv.

Gu, Yuan, Joshi, Neha S., Profit, Jochen, Frymoyer, Adam, Flaherman, Valerie J., Lee, Henry C. (2025). Infants Born at Late Preterm Gestation: Management during the Birth Hospitalization . The Journal of Pediatrics.

Yuan Gu, Chao Ma, Ziyang Wang (2024). TriConvUNeXt: A Pure CNN-Based Lightweight Symmetrical Network for Biomedical Image Segmentation . Journal of Imaging Informatics in Medicine.

Yuan Gu, Yasutoshi Kuboki, Takafumi Koyama, Nobuaki Matsubara, Yoichi Naito, Shunsuke Kondo, Kenichi Harano, Kan Yonemori, Kiyotaka Yoh, Tetsuya Mita, et al. (2024). PD‐1 inhibition with retifanlimab and/or arginase inhibition with INCB001158 in Japanese patients with solid tumors: A phase I study . Cancer Medicine.

Gu, Yuan, Ma, Chao, Wang, Ziyang (2024). TriConvUNeXt: A Pure CNN-Based Lightweight Symmetrical Network for Biomedical Image Segmentation . Journal of Imaging Informatics in Medicine.

Gu, Yuan, Kuboki, Yasutoshi, Koyama, Takafumi, Matsubara, Nobuaki, Naito, Yoichi, Kondo, Shunsuke, Harano, Kenichi, Yonemori, Kan, Yoh, Kiyotaka, Mita, Tetsuya, et al. (2024). PD-1 inhibition with retifanlimab and/or arginase inhibition with INCB001158 in Japanese patients with solid tumors: A phase I study . Cancer Medicine.

Yuan Gu, Mingyue Wang, Yishu Gong, Xin Li, Ziyang Wang, Yuli Wang, Song Jiang, Dan Zhang, Chen Li (2023). Unveiling Breast Cancer Risk Profiles: A Survival Clustering Analysis Empowered by an Online Web Application . Future Oncology.

Yuan Gu, Yoshie Tomozumi Nakamura, Hecheng Jin, Deyang Yu, Jessica Hinshaw, Rehan Rehman (2023). Introducing neuroscience methods: an exploratory study on the role of reflection in developing leadership from a HRD perspective . Human Resource Development International.

Yuan Gu, Yasir Hameed, Mohsen Nabi-Afjadi, Long Wu(2023). Cell membrane-coated nanoparticles for cancer therapy . Cancer Insight. 2. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 145–162.

Yuan Gu, Yasir Hameed, Mohsen Nabi-Afjadi, Long Wu (2023). Cell membrane-coated nanoparticles for cancer therapy . Cancer Insight.

Yuan Gu, Yasir Hameed, Mohsen Nabi-Afjadi, Long Wu (2023). Cell membrane-coated nanoparticles for cancer therapy . Cancer Insight.

Yuan Gu, Long Wu, Yasir Hameed, Mohsen Nabi-Afjadi(2023). Overcoming the challenge: cell-penetrating peptides and membrane permeability . Biomaterials and Biosensors. 2. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 16--41. Anser Press Pte. Ltd.

Yuan Gu, Jiang Song, Ela Kumar(2023). Chest Disease Image Classification Based on Spectral Clustering Algorithm . Research Reports on Computer Science. 2. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 77–90.

Yuan Gu, Jiang Song, Ela Kumar (2023). Chest Disease Image Classification Based on Spectral Clustering Algorithm . Research Reports on Computer Science.

Yuan Gu, Jiang Song, Ela Kumar(2023). Chest Disease Image Classification Based on Spectral Clustering Algorithm . Research Reports on Computer Science. 2. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 77–90.

Yuan Gu, Song Jiang, Ela Kumar(2023). Stroke Risk Prediction Using Artificial Intelligence Techniques Through Electronic Health Records . Artificial Intelligence Evolution. 4. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 88–98.

Yuan Gu, Song Jiang, Ela Kumar (2023). Stroke Risk Prediction Using Artificial Intelligence Techniques Through Electronic Health Records . Artificial Intelligence Evolution.

Yuan Gu, Song Jiang, Ela Kumar(2023). Stroke Risk Prediction Using Artificial Intelligence Techniques Through Electronic Health Records . Artificial Intelligence Evolution. 4. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 88–98.

Magnetic Resonance Imaging (MRI) Brain Tumor Image Classification Based on Five Machine Learning Algorithms @article{Song Jiang_Yuan Gu_Ela Kumar_2023, title={Magnetic Resonance Imaging (MRI) Brain Tumor Image Classification Based on Five Machine Learning Algorithms}, volume={4}, url={https://ojs.wiserpub.com/index.php/CCDS/article/view/2740}, DOI={10.37256/ccds.4220232740}, abstractNote={<p>With the emergence of new technologies, vast amounts of data have become pervasive in various aspects of social life, including public transportation, community services, and scientific research. As the population ages, healthcare has become increasingly crucial, and reducing the public burden, especially in hospitals, has become an urgent issue. For instance, manually managing vast electronic medical files, such as MRI images, based on their types is practically impossible. However, accurate classification is fundamental and critical for subsequent tasks, such as diagnosis. In this article, we utilized machine learning techniques to classify MRI brain tumor images. We employed a range of machine learning models, including k-Nearest Neighbors (k-NN), decision tree, Support Vector Machine (SVM), logistic regression, and Stochastic Gradient Descent (SGD). The performance of each model type was measured by True Skill Statistics (TSS), based on the results obtained from the confusion matrix. The results showed that k-NN works most efficiently among all those classification models. However, due to the constraints of limited running time and computational power, further investigation of the models and parameter optimization are necessary for future work.</p>}, number={2}, journal={Cloud Computing and Data Science}, author={Song Jiang and Yuan Gu and Ela Kumar}, year={2023}, month={May}, pages={122–133} } . Cloud Computing and Data Science.

Gu, Yuan, Nakamura, Yoshie Tomozumi, Jin, Hecheng, Yu, Deyang, Hinshaw, Jessica, Rehman, Rehan (2022). Introducing neuroscience methods: an exploratory study on the role of reflection in developing leadership from a HRD perspective . Human Resource Development International.

Gu, Yuan, Sachdev, Vandana, Tian, Xin, Nichols, James, Sidenko, Stanislav, Li, Wen, Beri, Andrea, Layne, W. Austin, Allen, Darlene, Wu, Colin O., et al. (2021). A phenotypic risk score for predicting mortality in sickle cell disease . British Journal of Haematology.

Gu, Yuan, Domanski, Michael J., Tian, Xin, Wu, Colin O., Reis, Jared P., Dey, Amit K., Zhao, Lihui, Bae, Sejong, Liu, Kiang, Hasan, Ahmed A., et al. (2020). Time Course of LDL Cholesterol Exposure and Cardiovascular Disease Event Risk . JACC: Journal of the American College of Cardiology.

Gu, Yuan, Xin, Victoria, Dandi, Gauri, Gani, Nuha, Mallick, Zyannah, Atkinson, Ian, Husain, Anwar, Ashraf, Adrita, Ciurea, Rodica, Tian, Xin, et al. (2020). USE OF MACHINE LEARNING METHODOLOGY TO FIND PREDICTORS OF ALL-CAUSE MORTALITY IN PREVENTION OF EVENTS WITH ANGIOTENSIN-CONVERTING ENZYME INHIBITION (PEACE) TRIAL . JACC: Journal of the American College of Cardiology.

Gu, Yuan, Sachdev, Vandana, Nichols, James, Li, Wen, Sidenk, Stanislav, Allen, Darlene, Wu, Colin, Thein, Swee Lay (2019). A Machine Learning Algorithm to Improve Risk Assessment for Patients with Sickle Cell Disease . Blood.

Gu, Yuan, Dandi, Gauri, Dey, Amit, Shalhoub, Ruba, Wang, Runqiu, Wu, Colin, Tian, Xin, Almario, Eileen Navarro, Patel, Tejas, Fleg, Jerome, et al. (2019). IDENTIFYING PREDICTORS OF HOSPITALIZATION DUE TO HEART FAILURE IN THE TOPCAT TRIAL USING MACHINE LEARNING TECHNIQUES . JACC: Journal of the American College of Cardiology.

Gu, Yuan, Hoque, Laboni H., Dey, Amit, Xin, Victoria, Shalhoub, Ruba, Wang, Runqiu, Wu, Colin, Xin, Tian, Almario, Eileen Navarro, Patel, Tejas, et al. (2019). PREDICTORS OF ALL-CAUSE MORTALITY IN THE AIM-HIGH TRIAL IDENTIFIED BY MACHINE LEARNING . JACC: Journal of the American College of Cardiology.

Gu, Yuan, Mallick, Zyannah, Dey, Amit, Shalhoub, Ruba, Wang, Runqiu, Wu, Colin, Tian, Xin, Almario, Eileen Navarro, Patel, Tejas, Fleg, Jerome, et al. (2019). PREDICTORS OF ALL-CAUSE MORTALITY IN THE BARI 2D TRIAL IDENTIFIED BY MACHINE-LEARNING . JACC: Journal of the American College of Cardiology.

Gu, Yuan, Xin, Victoria, Dey, Amit, Wang, Runqiu, Shalhoub, Ruba, Wu, Colin, Tian, Xin, Patel, Tejas, Fleg, Jerome, Kettermann, Anna, et al. (2019). Predictors of Hard Outcomes in the ALLHAT Trial Identified With Machine Learning . Arteriosclerosis, Thrombosis, and Vascular Biology.

Gu, Yuan, Cure-Cure, Carlos A., Cure, Pablo, Tian, Xin, Patel, Tejas, Wu, Colin O., Sviglin, Helena, Sopko, George, Csako, Gyorgy, Cody, Sean, et al. (2018). Predictors of All Cause Mortality and Their Gender Differences in a Hispanic Population From Barranquilla-Colombia Using Machine Learning With Random Survival Forests . Circulation.

PREPRINT

Yuan Gu, Silas Boye Nissen, Alexis T. Weiner, Kaye Suyama, Pablo Sanchez Bosch, Song Song, Alexander R. Dunn, Jeffrey D. Axelrod (2024). Cluster Assembly Dynamics Drive Fidelity of Planar Cell Polarity Polarization .

Yishu Gong, Yuli Wang, Ziyang Wang, Xin Li, Yuan Gu (2023). Longitudinal Analysis of Step Counts in Parkinson’s Disease Patients: Insights from a Web-Based Application .

Yuan Gu, Yishu Gong, Mingyue Wang, Song Jiang, Chen Li, Zheng Yuan (2023). Enhancing Kidney Failure Analysis: Web Application Development for Longitudinal Trajectory Clustering .

Yuan Gu, Mingyue Wang, Yishu Gong, Song Jiang, Chen Li, Dan Zhang (2023). Unveiling Breast Cancer Risk Profiles: A Comprehensive Survival Clustering Analysis Empowered by an Online Web Application for Personalized Medicine .