An IoT and artificial intelligence-based patient care system focused on COVID-19 pandemic. (28th December 2021) - Goar, Vishal Kumar; Yadav, Nagendra Singh; Chowdhary, Chiranji Lal; P, Kumaresan; Mittal, Mohit
World Health Organization has declared COVID-19 a pandemic. Like many other epidemic outbreaks, the COVID-19 pandemic also faces significant challenges. The digital technology allowed healthcare professionals in identification and isolation to the source of the infection to prevent community transmission of the virus by remotely monitoring the COVID-19 infected patients. We proposed a prediction model using Orange Canvas Program by creating a local instance dataset of eight suspected individuals' measured body parameters. Furthermore, six machine learning classifiers such as KNN, DT, SVM, random forest, neural network and naive Bayes are implemented to train the model on the dataset and in predicting the COVID-19. The results show that the proposed machine learning model successfully detects COVID-19. The evaluation results show that the highest accuracy value is obtained with neural networks and SVM, however neural networks outperform in other statistical parameters besides the accuracy rate.