Yihao Wang
Papers
2
Total Citations
20
H-Index
2
About
Dr. Yihao Wang is a pioneering researcher at the intersection of computer vision and surgical robotics, whose work is transforming how surgical skill is evaluated in the operating room. His primary research focuses on developing deep learning models to automatically assess surgeon performance from video recordings of robotic-assisted procedures. Dr. Wang’s most influential work, “Evaluating robotic-assisted surgery training videos with multi-task convolutional neural networks” (2021, 16 citations), established a foundation for automated skill assessment using synthetic tissue. He then advanced this paradigm in his landmark 2023 study (4 citations), where he introduced fully convolutional segmentation and multi-task attention networks to evaluate surgeons performing actual robotic-assisted partial nephrectomies. By analyzing videos of tumor resection and renography steps, Dr. Wang’s cascaded neural network approach enables objective, scalable feedback that was previously only possible through expert human review. His contributions are particularly impactful for surgical training, offering a pathway to democratize high-quality skill assessment and improve patient outcomes. Dr. Wang’s work represents a critical step toward integrating artificial intelligence into real-time surgical education and quality assurance.
Research Focus
Key Achievements
Top Papers
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- 2