Role of Intelligent Techniques for Cyber-Physical Systems in Healthcare

The merging of computer and physical aspects is revolutionizing healthcare via Cyber-Physical Systems (CPS). The capabilities and security of CPS are enhanced by machine learning, AI, and data analytics. The data collected and analyzed by these systems comes from interconnected systems, medical equipment, and interactions with patients. Data analytics and predictive modeling allow CPS to find patterns and outliers in patient data, which speeds up disease diagnostics, predicts adverse occurrences, and develops personalized treatment programmes. Advanced algorithms in CPS enhance patient safety and care by continuously monitoring vital signs, medication doses, and responses in real time. Secure data exchange, backed by anomaly detection tools and secure communication mechanisms, is crucial for networked CPS to protect patient information. By analyzing past data, predicting future patient flow, and allocating resources efficiently, decision support systems within CPS optimize healthcare resources, leading to improved operational efficiency and cost savings. The chapter highlights the necessity for inventive techniques to overcome the inherent complexity of healthcare CPS while covering the most significant components and aspects. Next, it delves into the ways in which intelligent methods, such as decision support systems, predictive analytics, and real-time monitoring, could enhance healthcare CPS. It looks at the benefits and drawbacks of each use, as well as recent developments and market trends. Cybersecurity and the preservation of patient data are two of the healthcare CPS privacy and safety concerns covered in this chapter.