AI-Assisted Surgical Robotics: A Review of Current State and Future Possibilities

Abstract

By improving accuracy, decreasing human error, and permitting less invasive operations, artificial intelligence (AI)-assisted surgical robotics is transforming contemporary surgery. The integration of sophisticated algorithms like computer vision, machine learning, and deep learning approaches is the main emphasis of this paper, which examines the state of AI-driven surgical robotics today. Modern approaches like Convolutional Neural Networks (CNNs) for image-guided navigation and Reinforcement Learning (RL) for autonomous decision-making in surgical tasks are contrasted with traditional methods such as computer-assisted surgery algorithms. Modern AI techniques offer flexibility and continual learning, greatly enhancing results in complicated, real-time circumstances, while traditional systems perform best in organised environments with predefined tasks. The difficulties are also covered, including the necessity for strong legal frameworks, ethical issues, and data protection. Potential future developments include improved human-robot cooperation, fully autonomous surgical systems, and multi-modal data integration for customised surgery. In order to create the path for more successful and efficient surgical procedures, the paper ends by emphasising how AI-assisted surgical robotics has the potential to revolutionise healthcare.