Jiayi Ji

发表

Machine learning identifies novel blood protein predictors of penetrating and stricturing complications in newly diagnosed paediatric Crohn's disease

Judy H. Cho, M. Dubinsky, B. Sands, 2020, Alimentary pharmacology & therapeutics.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma.

Alexander R. Pico, Matthew A. Wyczalkowski, Sara R. Savage, 2021, Cancer cell.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

Guo Ci Teo, Matthew A. Wyczalkowski, Andy T. Kong, 2019, Cell.

Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II–III Melanoma

C. Morrison, M. Ernstoff, B. Taback, 2019, Clinical Cancer Research.

Tree‐Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level

Liangyuan Hu, Bian Liu, Yan Li, 2020, Journal of the American Heart Association.

Insights into Impact of DNA Copy Number Alteration and Methylation on the Proteogenomic Landscape of Human Ovarian Cancer via a Multi-omics Integrative Analysis*

Pei Wang, Kevin J. Gleason, Lin S. Chen, 2018, Molecular & Cellular Proteomics.

Longitudinal Autonomic Nervous System Measures Correlate With Stress and Ulcerative Colitis Disease Activity and Predict Flare.

B. Arnrich, M. Danieletto, J. Dudley, 2020, Inflammatory bowel diseases.

Factors associated with mammography use: A side‐by‐side comparison of results from two national surveys

M. Mazumdar, E. Taioli, M. besculides, 2020, Cancer medicine.

Gestational Diabetes, Subsequent Type 2 Diabetes, and Food Security Status: National Health and Nutrition Examination Survey, 2007–2018

Ryung S. Kim, Lihua Li, Jee-Young Moon, 2022, Preventing chronic disease.

Effects of school breaks on influenza-like illness incidence in a temperate Chinese region: an ecological study from 2008 to 2015

Xiling Wang, G. Qin, Y. Chu, 2017, BMJ Open.

Programmed Death-1 or Programmed Death Ligand-1 Blockade in Patients with Platinum-resistant Metastatic Urothelial Cancer: A Systematic Review and Meta-analysis.

M. Mazumdar, W. Oh, M. Galsky, 2019, European urology.

Machine learning to identify and understand key factors for provider-patient discussions about smoking

Liangyuan Hu, Lihua Li, J. Ji, 2020, Preventive medicine reports.

Estimating heterogeneous survival treatment effect in observational data using machine learning

Fan Li, Liangyuan Hu, Jiayi Ji, 2020, Statistics in medicine.

Estimation of causal effects of multiple treatments in observational studies with a binary outcome

Michael J. Lopez, Liangyuan Hu, J. Wisnivesky, 2020, Statistical methods in medical research.

Immunotherapy Outcomes in Individuals With Non–Small Cell Lung Cancer and Poor Performance Status

Liangyuan Hu, J. Wisnivesky, M. Kale, 2022, JNCI cancer spectrum.

Insights into Impact of DNA Copy Number Alteration and Methylation on the Proteogenomic Landscape of Human Ovarian Cancer via a Multi-omics Integrative Analysis.

Kevin J. Gleason, Lin S. Chen, J. Martignetti, 2019, Molecular & cellular proteomics : MCP.

A Flexible Approach for Assessing Heterogeneity of Causal Treatment Effects on Patient Survival Using Large Datasets with Clustered Observations

Liangyuan Hu, Hao Liu, Jiayi Ji, 2022, International journal of environmental research and public health.

A flexible approach for causal inference with multiple treatments and clustered survival outcomes

J. Hogan, Liangyuan Hu, R. Ennis, 2022, Statistics in medicine.

Joint marginal structural models to estimate the causal effects of multiple longitudinal treatments in continuous time with application to COVID-19

Erick R. Scott, Fan Li, Liangyuan Hu, 2021 .

Estimating Heterogeneous Survival Treatment Effect via Machine/Deep Learning Methods in Observational Studies

Fan Li, Liangyuan Hu, Jiayi Ji, 2020 .

Variable selection with missing data in both covariates and outcomes: Imputation and machine learning

Liangyuan Hu, Jung-Yi Joyce Lin, Jiayi Ji, 2021, Statistical methods in medical research.

A FLEXIBLE SENSITIVITY ANALYSIS APPROACH FOR UNMEASURED CONFOUNDING WITH MULTIPLE TREATMENTS AND A BINARY OUTCOME WITH APPLICATION TO SEER-MEDICARE LUNG CANCER DATA.

Michael J. Lopez, Liangyuan Hu, M. Kale, 2020, The annals of applied statistics.

ProTrack: An Interactive Multi‐Omics Data Browser for Proteogenomic Studies

Francesca Petralia, Pei Wang, Anna Pamela Calinawan, 2020, Proteomics.

A role for CXCR3 ligands as biomarkers of post-operative Crohn's disease recurrence.

J. Rioux, M. Silverberg, R. Duerr, 2021, Journal of Crohn's & colitis.

Identifying and understanding determinants of high healthcare costs for breast cancer: a quantile regression machine learning approach

Liangyuan Hu, Lihua Li, Mark Sanderson, 2020, BMC Health Services Research.

Identifying and assessing the impact of key neighborhood-level determinants on geographic variation in stroke: a machine learning and multilevel modeling approach

Liangyuan Hu, Bian Liu, Yan Li, 2020, BMC Public Health.

Quantile Regression Forests to Identify Determinants of Neighborhood Stroke Prevalence in 500 Cities in the USA: Implications for Neighborhoods with High Prevalence

Liangyuan Hu, Bian Liu, Yiyi Zhang, 2020, Journal of Urban Health.

A flexible sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome

Liangyuan Hu, Chenyang Gu, Jiayi Ji, 2020 .

Estimating the causal effects of multiple intermittent treatments with application to COVID-19

Liangyuan Hu, Himanshu Joshi, Fan Li, 2021, ArXiv.

CIMTx: An R Package for Causal Inference with Multiple Treatments using Observational Data

Liangyuan Hu, J. Ji, Jiayi Ji, 2021, R J..

Quantile regression forests to identify determinants of stroke: implications for neighborhoods with high prevalence

Liangyuan Hu, Bian Liu, Yan Li, 2020 .

Determinants of total end-of-life healthcare costs of Medicare beneficiaries: A quantile regression forests analysis.

M. Mazumdar, Liangyuan Hu, Lihua Li, 2021, The journals of gerontology. Series A, Biological sciences and medical sciences.