AI-Based Intelligent Model to Predict Epidemics Using Machine Learning Technique
Liaqat Ali, Saif E. A. Alnawayseh, Mohammed Salahat, Taher M. Ghazal, Mohsen A. A. Tomh, Beenu Mago
Abstract
The immediate international spread of severe acute respiratory syndrome revealed the potential threat of infectious diseases in a closely integrated and interdependent world. When an outbreak occurs, each country must have a well-coordinated and preventative plan to address the situation. Information and Communication Technologies have provided innovative approaches to dealing with numerous facets of daily living. Although intelligent devices and applications have become a vital part of our everyday lives, smart gadgets have also led to several physical and psychological health problems in modern society. Here, we used an artificial intelligence AI-based system for disease prediction using an Artificial Neural Network (ANN). The ANN improved the regularization of the classification model, hence increasing its accuracy. The unconstrained optimization model reduced the classifier’s cost function to obtain the lowest possible cost. To verify the performance of the intelligent system, we compared the outcomes of the suggested scheme with the results of previously proposed models. The proposed intelligent system achieved an accuracy of 0.89, and the miss rate 0.11 was higher than in previously proposed models.