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Dynamic model updating (DMU) approach for statistical learning model building with missing data.

Rahi JainWei Xu
Published in: BMC bioinformatics (2021)
DMU approach provides an alternative to the existing approaches of information elimination and imputation in processing the datasets with missing values. While the study applied the approach for continuous cross-sectional data, the approach can be applied to longitudinal, categorical and time-to-event biological data.
Keyphrases
  • cross sectional
  • electronic health record
  • big data
  • healthcare
  • working memory
  • deep learning
  • artificial intelligence