Abstract
This study addresses the missing data problem in the large-scale medical dataset MIMIC-IV, especially in situations where intubation-extubation events are paired. We employed a strategy involving patient scenario works that checked the temporal order and logical links of intubation/extubation data, and seven reconstruction rules for handling missing values. Through this, we reduced the overall loss rate from 36.89% (3321 records) to 13.37% (1204 records) and achieved a 37.26% data increase (+2117 records) compared to before reconstruction(6582).
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