Extremely missing numerical data in Electronic Health Records for machine learning can be managed through simple imputation methods considering informative missingness: A comparative of solutions in a COVID-19 mortality case study.
Pablo Ferri BorredaNekane Romero-GarciaRafael BadenesDavid Lora-PablosTeresa García MoralesAgustín Gómez De La CamaraJuan M. García-GómezCarlos SáezPublished in: Comput. Methods Programs Biomed. (2023)
Keyphrases
- numerical data
- missing values
- missing data
- imputation methods
- machine learning
- electronic health records
- data sets
- feature selection
- incomplete data
- learning algorithm
- machine learning algorithms
- categorical data
- pattern recognition
- clinical data
- data quality
- database
- clinical trials
- medical data
- data analysis
- decision trees
- high dimensional data
- text classification
- text mining
- information extraction