Papers
3
Total Citations
28
H-Index
2
About
Surong Hua is a leading researcher in the field of surgical innovation, with a primary focus on the application of artificial intelligence in minimally invasive procedures. Their work centers on developing and validating deep learning models, particularly Convolutional Neural Networks, for the real-time recognition and localization of surgical tools in both endoscopic and robotic settings. Hua’s major contributions include pioneering a robust strategy for tool tip identification across multiple surgical scenarios, a breakthrough that enhances intraoperative safety and precision. Their most cited work, "Application and evaluation of surgical tool and tool tip recognition based on Convolutional Neural Network in multiple endoscopic surgical scenarios" (2023), has garnered 18 citations, underscoring its foundational impact on computer-assisted surgery. Additionally, Hua has conducted detailed analyses of learning phases in robotic and endoscopic thyroidectomy, providing critical insights into surgical training and outcomes. With recent work in 2025 further advancing tool localization strategies, Hua continues to shape the future of smart operating rooms, bridging the gap between AI and surgical practice. Their research is essential reading for students and professionals interested in the intersection of machine learning and surgical robotics.
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