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Abstract

Abstract: This research, aimed at identifying patterns of COVID-19 symptoms, was conducted using predictive models based on Artificial Neural Networks (ANNs). Data from 6,512 patients was taken from the Kaggle platform. Based on state-of-the-art data, three base models were created and modified with up to four different configurations each. Five experiments were performed for each configuration, resulting in a total of seventy-five experiments. Of all these, base model number two stood out, achieving an F1 score of 0.8806, an AUC-ROC of 0.9472, and an accuracy of 88.8% metrics superior to the other models and sufficiently relevant for medical predictions. With this model, a computer system was implemented with a web application deployed in the cloud that allows any user to access and make a prediction from any web browser.