Fusion Based Self Diagnosis Expert System Empowered with Leven-berg Marquardt Algorithm

COVID-19 coronavirus disease is the latest virus in the new century. The World Health Organization- WHO organization announced that COVID-19 disease is a pandemic that leads to thousands of death in short time of spam. A quick and accurate diagnosis of COVID-19 shows an important role in its prevention. This study is based on a fusion-based Self-Diagnosis Expert System Empowered by the Leven-berg Marquardt Algorithm for the diagnosis of diseases. Leven-berg Marquardt has been implemented for the classification of different symptoms of the diseases and relates the results for their diagnosis. The MatLab software was used for the simulation purpose. The proposed fusion-based LB increased the accuracy in the training and validation process to be 10 times more efficient than the existing. The fusion technique achieved an overall accuracy of 98.86%, and 99.09% in all performance metrics which included TNR, precision, and FPR statistical parameters.