During outbreaks of infectious diseases, such as COVID-19, it is critical to rapidly determine
treatment priorities and identify patients requiring hospitalization based on clinical severity …

Background The application of machine learning (ML) to analyze clinical data with the goal
to predict patient outcomes has garnered increasing attention. Ensemble learning has been …

Currently, since there are still some inconsistencies in the severity data types of COVID‐19
among different hospitals or sources [8], we aimed to establish a consistent severity score for …

The recent COVID-19 pandemic had wreaked havoc worldwide, causing a massive strain on
already-struggling healthcare infrastructure. Vaccines have been rolled out and seem …

Objective Risk prediction models are widely used to inform evidence-based clinical decision
making. However, few models developed from single cohorts can perform consistently well …

Currently, individual artificial intelligence (AI) algorithms face significant challenges in
effectively diagnosing and predicting early stage emerging serious diseases. Our …

Introduction A prompt severity assessment model of patients with confirmed infectious
diseases could enable efficient diagnosis while alleviating burden on the medical system …

Rationale: Prognostic tools for aiding in the treatment of hospitalized COVID-19 patients
could help improve outcome by identifying patients at higher or lower risk of severe disease …

Computed Tomography (CT) scans provide a detailed image of the lungs, allowing
clinicians to observe the extent of damage caused by COVID-19. The CT severity score …

Recent outbreak of the COVID-19 pandemic in December 2019 has witnessed a rapid
spread from Wuhan, China, to all over the world. This highly transmittable infectious disease …