Researchers from the National Institute of Health Data Science at Peking University and the Department of Clinical Epidemiology and Biostatistics at Peking University People's Hospital have conducted ...

Missing data present a perennial challenge in scientific research, potentially undermining the validity of conclusions if not addressed rigorously. The analysis of missing data encompasses a broad ...

Missing data imputation is a critical process in data analysis, enabling researchers to infer plausible values for absent observations. Over recent decades, a variety of methods have emerged, ranging ...

Overview: Machine learning failures usually start before modeling, with poor data understanding and preparation.Clean data, ...

Unlike other industries, healthcare generates not only numerical and categorical data but also large volumes of unstructured ...