AN INTELLIGENT ASSISTANT FOR PREDICTION POST-COVID SKIN ALLERGIES DIAGNOSIS
AbstractThe epidemic of COVID-19 provides various issues for healthcare professionals. Rapid assessment and treatment, vulnerability classification, efficient use of critical care facilities, adequate medications, surveillance, and prompt discharge, are crucial to protect as many casualties as possible. We described different classification techniques of ML (machine learning) to analyze skin-related issues. This research aims to provide adequate skin specialists with a strategic plan to understand that they may diagnose its prospects and problems. In this work, we use well-known ML methods, including DT (Decision Tree), LR (Logistic Regression), SVM (Support Vector Machines), KNN (K Nearest Neighbor), and multi-model (Gradient, gaussian nave bias, XGB, SGD), classification methods. Make an intelligent diagnostic assistant to correctly identify a certain kind of allergy condition.
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