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Navigating the Ethical Landscape of AI-Driven Surgical Robots
0
Zitationen
3
Autoren
2025
Jahr
Abstract
Background Information: The development of surgical robotics ranges from early systems such as the PUMA 560 to more sophisticated platforms like da Vinci. Even with improvements in precision, human intervention is still essential. Integration of AI improves error reduction, accessibility, and autonomy. Objectives: Explainable AI, federated learning with blockchain, swarm intelligence, CNN-LSTM for anomaly detection, and ensemble learning are some of the hybrid AI techniques used in this study. Methods: The study aims to enhance the accuracy of surgery, anomalies, resource usage, and ethics for patient safety and data privacy. Result: The proposed method achieved 98.5% accuracy, 95.4% data privacy, 93% anomaly detection, 89.2% resource efficiency, and 87.9% ethical compliance. Conclusion: AI surgical robotics promote scalable and patient-centered healthcare solutions by accuracy, effectiveness, and ethics.
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