Data sets with missing observations are common in psychology research. One typically
analyzes such data by applying statistical methods that rely on the assumption that the …

Background Risk stratification helps guide appropriate clinical care. Our goal was to develop
and validate a broad suite of predictive tools based on International Classification of …

Primary care physicians are likely both excited and apprehensive at the prospects for
artificial intelligence (AI) and machine learning (ML). Complexity science may provide …

Machine learning methods have been a standard approach to select features that are
associated with an outcome and to build a prediction model when the number of candidate …

Electronic health records (EHRs) provide meaningful knowledge of drug‐related adverse
events (AEs) that are not captured in standard drug development and postmarketing …

Background Electronic health record (EHR) prediction models may be easier to use in busy
clinical settings since EHR data can be auto-populated into models. This study assessed …

Objective This study aimed to develop and validate a mortality risk prediction model for older
people based on the Chinese Longitudinal Healthy Longevity Survey using the stacking …

Oesophagectomy for cancer of the oesophagus carries significant morbidity and mortality.
Ninety-day mortality and anastomosis leakage are critical early postoperative problems …

Les infections infantiles constituent une problématique majeure en termes de morbi-
mortalité à l'échelle mondiale, contribuant significativement aux décès infantiles, notamment …