A Simulated Proposed Model for Black Fungus Detection by using Fuzzy Logic

Recently, some diseases and health problems have appeared that threaten human health.There is a global interest for knowing and preventing spread of pandemic diseases.At the top of importance after COVID-19 is now its different consequences such as Black Fungus that represents an unknown disease for the common.Black Fungus related to people who has low immunity.This research presents an overview of its characteristics, symptoms, and shape that will be manifested in the patient's body.Unfortunately, the shape of Black Fungus in body can be observed interiorly or exteriorly.The aim and scope of this research is to decompose the complexity of Black Fungus detection into five phases that covers all the forms of Black Fungus.Furthermore, a simulated fuzzy model of Black Fungus detection is presented, with the dependency on a proposed facial disease detection model.This model can be used to prove the relationship between post-Corona and Black Fungus patients.The proposed model can differentiate between the measure of Black Fungus infection risk and COVID-19 in an accurate way.Finally, this research helps in defeating the spread of side effects that may appear.