Emerging Utility of Artificial Intelligence Driven Medical Robots in Health Care: A Review

The incorporation of Artificial Intelligence (AI) into medical robotics has transformed contemporary healthcare by improving precision, efficiency, and personalization in clinical treatments. This paper offers a thorough examination of AI-driven medical robots, emphasizing their transformative capabilities in diagnosis, surgery, rehabilitation, and patient care. Artificial intelligence algorithms, especially those utilizing machine learning and deep learning frameworks, empower medical robots to execute intricate tasks, including image-guided surgery, self-navigating, making decisions in real time, and adaptive learning. Surgical robots integrated with AI enhance minimally invasive treatments by providing exceptional precision and minimizing patient trauma, whereas diagnostic robots facilitate early illness identification through pattern recognition in imaging and genetic data. Rehabilitation robots, equipped with AI, provide personalized therapy by continuously assessing and adjusting to the patient's advancement. Moreover, socially helpful robots employ natural language processing (NLP) and affective computing to aid elderly and disabled patients via interactive care. Notwithstanding these gains, problems endure, encompassing ethical dilemmas, data privacy issues, regulatory adherence, and the necessity for rigorous validation in clinical environments. The paper examines the present state of AI-driven medical robotic systems, assesses ongoing clinical trials, and considers future trajectories, highlighting the imperative for cross-disciplinary cooperation among engineers, data scientists, physicians, and legislators. This study objectively evaluates the features and limitations of AI-driven medical robots, highlighting their significance as essential instruments in advancing precision medicine and transforming the global healthcare landscape through intelligent automation and improved patient-centred solutions.