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Personalized Risk Prediction for Cancer Survivors: A Bayesian Semi-parametric Recurrent Event Model with Competing Outcomes
View ORCID ProfileNam H Nguyen, Seung Jun Shin, Elissa B Dodd-Eaton, Jing Ning, View ORCID ProfileWenyi Wang
doi: https://doi.org/10.1101/2023.02.28.530537
Nam H Nguyen
aDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX
bDepartment of Statistics, Rice University, Houston, TX
Seung Jun Shin
cDepartment of Statistics, Korea University, Seoul, Korea
Elissa B Dodd-Eaton
aDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX
Jing Ning
dDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX
Wenyi Wang
aDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX
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Posted March 06, 2023.
Personalized Risk Prediction for Cancer Survivors: A Bayesian Semi-parametric Recurrent Event Model with Competing Outcomes
Nam H Nguyen, Seung Jun Shin, Elissa B Dodd-Eaton, Jing Ning, Wenyi Wang
bioRxiv 2023.02.28.530537; doi: https://doi.org/10.1101/2023.02.28.530537
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