Abstract

This article introduces a novel approach in developing an artificial intelligence (AI) driven prediction model, named the Random Forest COVID-19 Predictor, for accurately forecasting COVID-19 infections. The primary aim of this model is to provide timely support for clinical decision-making by leveraging predictive analytics on real patient data. With the urgent need to understand and effectively treat this new disease, coupled with resource constraints during a pandemic, accurate prediction models play a crucial role in guiding resource allocation decisions. Through extensive simulation experiments, the Random Forest COVID-19 Predictor demonstrates superior precision compared to existing models, making it a promising tool for enhancing clinical decision support during the ongoing COVID-19 pandemic.

Description