A Proposed Approach for Monkeypox Classification

Public health concerns have been heightened by the emergence and spread of monkeypox, a viral disease that affects both humans animals. The significance early detection diagnosis monkeypox cannot be overstated, as it plays crucial role in minimizing negative impact on affected individuals safeguarding public health. Monkeypox poses considerable threat to human well-being, causing physical discomfort mental distress, while also posing challenges work productivity. This study proposes an applied model combines deep learning models such as: ResNet-50, VGG16, MobileNet machine Random Forest Classifier, K-Nearest Neighbors Gaussian Naive Bayes Decision Tree Logistic Regression AdaBoost Classifier classify detect monkeypox. datasets are used this research Skin Lesion Dataset (MSLD) Image (MID) total 659. Subjects range from healthy cases severe skin lesions. test results show which achieves positive results, with Accuracy being 0.97 F1-score 0.98.