The wave of monkeypox and recent worries underscore the need for fast, specific diagnostic tools. While being effective, traditional diagnostic methods often are time consuming and involve use of precious resources. The use of AI to drive medical image analysis in monkeypox is the focus of this research into the recent advancements in AI driven medical image analysis. In this study, we compared existing literature and in particular pinpointed key research papers utilizing machine learning and deep learning techniques to detect monkeypox lesions. We presented a detailed analysis of these studies, including their datasets, methodologies, outcome, and limitations, and listed some of the publicly available datasets of monkeypox. This paper highlights the potential of learning models in monkeypox diagnosis which in future recommend for continued research to optimize clinical applications.