Papers
3
Total Citations
100
H-Index
2
About
Dimitrios Anastasiou is a leading researcher at the intersection of artificial intelligence and robotic surgery, with a primary focus on developing objective, automated methods for assessing surgical technical skills. His work addresses a critical gap in surgical training: the need for standardized, unbiased evaluation tools that can replace subjective human assessment. Anastasiou’s major contributions include pioneering the use of deep learning and contrastive regression architectures for video-based skill evaluation. His highly cited 2023 systematic review (71 citations) provides a comprehensive roadmap of existing objective assessment tools, establishing a benchmark for the field. He further advanced the domain with the novel Contra-Sformer model (28 citations), which compares surgical performance against reference videos to capture subtle differences in technique. Most recently, his 2025 work on deep learning prediction of surgical skills and technical errors in robotic-assisted gynaecological surgery demonstrates the practical application of his methods. By combining rigorous systematic review with cutting-edge AI model development, Anastasiou is shaping the future of surgical accreditation and training, making robotic surgery safer and more consistent through data-driven performance metrics.
Research Focus
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