An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.
COVID-19 severity can be predicted by a model with 5 variables: respiratory rate, systolic blood pressure, plasma albumin, LDH, and CRP.
Machine learning models estimated the probability of developing sepsis in children admitted to the emergency department.
Background Tobacco use among United States (US) youth and young adults has declined from historic levels, but cannabis use ...
Background Anti-C1q autoantibodies can disrupt normal complement function, contributing to the formation of pathogenic immune ...
Objective This study aimed to determine the proportion of capacity challenges for refusal of care, the risk factors that may trigger challenges to capacity and to consider the implications of ...
Introduction Antimicrobial resistance (AMR) is a pressing global health problem disproportionately affecting low- and ...
Background Blood culture (BC) in children has relatively low diagnostic yield and high contamination rates, limiting ...
Background Smoke-free and aerosol-free households (SAFHs) reduce exposure to secondhand smoke and aerosol and support ...
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