The paper "AI-Based Approaches for the Diagnosis of Mpx: Challenges and Future Prospects" provides a comprehensive exploration of the detection and classification of Mpx, a zoonotic viral disease. The authors introduce the subject, outline research objectives, and discuss the historical context and epidemiology of Mpx. They delve into the fundamental concepts of medical imaging, various imaging techniques, machine learning (ML) applications, convolutional neural networks (CNNs), and model evaluation metrics. The study highlights the systematic approach used in the literature review and emphasizes the importance of benchmark datasets. It examines diverse AI-based methodologies, including both ML and deep learning (DL) approaches, and addresses the challenges inherent in these methodologies. The paper concludes with an exploration of future prospects, aiming to provide a robust framework for advancing the diagnosis and management of Mpx outbreaks. Key aspects covered include the clinical presentation, diagnostic methods such as PCR and imaging, and the role of ML classifiers in predicting and managing Mpx outbreaks.The paper "AI-Based Approaches for the Diagnosis of Mpx: Challenges and Future Prospects" provides a comprehensive exploration of the detection and classification of Mpx, a zoonotic viral disease. The authors introduce the subject, outline research objectives, and discuss the historical context and epidemiology of Mpx. They delve into the fundamental concepts of medical imaging, various imaging techniques, machine learning (ML) applications, convolutional neural networks (CNNs), and model evaluation metrics. The study highlights the systematic approach used in the literature review and emphasizes the importance of benchmark datasets. It examines diverse AI-based methodologies, including both ML and deep learning (DL) approaches, and addresses the challenges inherent in these methodologies. The paper concludes with an exploration of future prospects, aiming to provide a robust framework for advancing the diagnosis and management of Mpx outbreaks. Key aspects covered include the clinical presentation, diagnostic methods such as PCR and imaging, and the role of ML classifiers in predicting and managing Mpx outbreaks.