The R package rcssci offers an intuitive solution for visualizing Restricted Cubic Splines (RCS) in regression analyses. It automates the generation of spline plots for outcomes like odds ratios (OR), hazard ratios (HR), and risk ratios (RR), facilitating the identification of non-linear relationships in data. Supporting Cox, Logistic, linear, and quasi-Poisson models, rcssci aids researchers in interpreting complex data relationships before delving into advanced machine learning techniques.

 A first-of-its-kind global-to-local study has found that COVID-19’s impact varied remarkably across 920 locations worldwide, even within the same country. By analyzing data on cases, deaths, and healthy years lost between 2020 and 2021, the researchers revealed that broad national or regional averages may mask substantial local disparities. The study calls for more detailed, location-specific data to guide better public health decisions in future pandemics.

A new study introduces an AI-integrated dynamic biomarker system that detects early disease tipping points and classifies thyroid cancer into actionable subtypes, paving the way for precision diagnosis and treatment.