Background Rheumatic heart disease (RHD) remains a major cause of morbidity and mortality in low-resource settings, ...

Abstract: Classification of missing data based on estimation is still challenging since existing methods relying on one imputation strategy fail to consider the diversity of different attribute ...

One seismometer is often not enough to reliably detect earthquakes or human activity such as underground nuclear tests.

The Census Bureau is planning for 2030, making decisions that will shape the distribution of federal funding that topped $2.8 trillion in fiscal year 2021, even ...

The rbmi package is used for the imputation of missing data in clinical trials with continuous multivariate normal longitudinal outcomes. It supports imputation under a missing at random (MAR) ...

This study introduces an XGBoost-MICE (Multiple Imputation by Chained Equations) method for addressing missing data in mine ventilation parameters. Using historical ventilation system data from ...

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 ...

Abstract: Survival analysis is the method of finding the time of occurrence of an event. Survival analysis is used as a prognostic tool in healthcare especially in diagnosing cancer. Any healthcare ...

ABSTRACT: Missing data presents a significant challenge in statistical analysis and machine learning, often resulting in biased outcomes and diminished efficiency. This comprehensive review ...

Data is almost always incomplete. Patients drop out of clinical trials and survey respondents skip questions; schools fail to report scores, and governments ignore elements of their economies. When ...