Dataset Information

CondiS web app: imputation of censored lifetimes for machine learning-based survival analysis.

ABSTRACT:

Summary

In the era of big data, machine learning techniques are widely applied to every area in biomedical research including survival analysis. It is well recognized that censoring, which is a common missing issue in survival time data, hampers the direct usage of these machine learning techniques. Here, we present CondiS, a web toolkit with graphical user interface to help impute the survival times for censored observations and predict the survival times for future enrolled patients. CondiS imputes a censored survival time based on its distribution conditional on its observed part. When covariates are available, CondiS-X incorporates this information to further increase the imputation accuracy. Users can also upload data of newly enrolled patients and predict their survival times. As the first web-app tool with an imputation function for censored lifetime data, CondiS web can facilitate conducting survival analysis with machine learning approaches.

Availability and implementation

CondiS is an open-source application implemented with Shiny in R, available free at: https://biostatistics.mdanderson.org/shinyapps/CondiS/.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Wang Y

PROVIDER: S-EPMC9438949 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

CondiS web app: imputation of censored lifetimes for machine learning-based survival analysis.

Wang Yizhuo Y Flowers Christopher R CR Li Ziyi Z Huang Xuelin X

Bioinformatics (Oxford, England) 20220901 17

<h4>Summary</h4>In the era of big data, machine learning techniques are widely applied to every area in biomedical research including survival analysis. It is well recognized that censoring, which is a common missing issue in survival time data, hampers the direct usage of these machine learning techniques. Here, we present CondiS, a web toolkit with graphical user interface to help impute the survival times for censored observations and predict the survival times for future enrolled patients. C ...[more]

PMID: 35801895

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Dataset Information

CondiS web app: imputation of censored lifetimes for machine learning-based survival analysis.

Summary

Availability and implementation

Supplementary information

Publications

CondiS web app: imputation of censored lifetimes for machine learning-based survival analysis.

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