Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack
of objective outcomes and fidelity metrics. AI technologies and specifically Natural …

Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …

Background The benefits and safety of the treatment of mild chronic hypertension (blood
pressure,< 160/100 mm Hg) during pregnancy are uncertain. Data are needed on whether a …

The global supply of COVID-19 vaccines remains limited. An understanding of the immune
response that is predictive of protection could facilitate rapid licensure of new vaccines. Data …

Background The food industry uses artificial sweeteners in a wide range of foods and
beverages as alternatives to added sugars, for which deleterious effects on several chronic …

Because missing data are present in almost every study, it is important to handle missing
data properly. First of all, the missing data mechanism should be considered. Missing data …

Importance Mediation analyses of randomized trials and observational studies can generate
evidence about the mechanisms by which interventions and exposures may influence health …

Missing data is a common occurrence in clinical research. Missing data occurs when the
value of the variables of interest are not measured or recorded for all subjects in the sample …

Objective To develop and validate a pragmatic risk score to predict mortality in patients
admitted to hospital with coronavirus disease 2019 (covid-19). Design Prospective …

Purpose To describe acute respiratory distress syndrome (ARDS) severity, ventilation
management, and the outcomes of ICU patients with laboratory-confirmed COVID-19 and to …