Neuro-Symbolic Robotics in Personalized Healthcare: From Diagnosis to Drug Delivery

Abstract

The integration of neuro-symbolic robotics into personalized healthcare represents a transformative approach to medical diagnostics, treatment planning, and drug delivery. By combining the adaptive learning capabilities of neural networks with the structured reasoning of symbolic AI, neuro-symbolic systems offer enhanced interpretability, robustness, and precision in clinical applications (Lu et al., 2024; Serrano, 2024). This paper explores the theoretical foundations, technological frameworks, and clinical implementations of neuro-symbolic robotics, emphasizing their role in advancing personalized medicine. Furthermore, ethical considerations, data privacy challenges, and future research directions are discussed to facilitate the safe and effective deployment of these systems in clinical settings.