This paper provides a bibliometric analysis study of recent developments in Medical Cyber-Physical Systems (MCPS), with a particular emphasis on explainable artificial intelligence (XAI) and formal modeling approaches. MCPS are crucial for advancing healthcare by seamlessly integrating physical and computational components to enhance patient care. However, ensuring that these systems are transparent and interpretable is vital, especially as they increasingly rely on AI-driven decision-making. Through a comprehensive bibliometric analysis, this study identifies publication trends, leading authors, prominent institutions, and emerging themes within the field of explainable MCPS. Additionally, we examine how formal modeling languages like SysML and AADL contribute to strengthening the reliability and interpretability of MCPS. The paper concludes by identifying key directions for future research, aiming to foster deeper insights and further innovation in this transformative area.