… In this paper, we begin with a comprehensive review of … , feature extraction, and the evaluation
metrics used to assess the … how missing values can be handled using mean imputation: …

… I critically evaluate Immunopred both quantitatively and using biomedically validated
literature; including healthy control and COVID disease data sets, and recommendations, to …

… to impute binary variables and predictive mean matching to impute numeric features. …
SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: …

… Therefore, the primary objective of this study was to evaluate and compare the performance
… to indicate statistical significance. We handled missing data by applying multiple imputations …

… multi-parameter fusion prediction of coal face gas concentration. We determined the
performance evaluation … smoothing method to impute missing items in the data. The approximate …

… , linear interpolation, spline interpolation, Stineman interpolation, Kalman filtering,
weighted moving average and multiple imputation by chained equation (MICE) models were …

… multiple imputation methods to address the foregoing data … However, the methods cannot
be extended to multi-parameter … In this section, we briefly review the basic results for the …

… cross-sectional data and compare the parameters between groups with two levels. To evaluate
… analysis, including imputation methods or combined with multiple imputation procedures. …

… Multi-parameter survival models can incorporate more … as multiple imputations by creating
a new imputation for … and need detailed evaluation to ensure that patient sensitive data are not …

… artery pressure monitoring systems, automated multi-parameter HF risk algorithms as ancillary
… Multiple imputation was applied to impute 20 possible values for each missing data entry …