Maurizio Pacilli
Papers
2
Total Citations
90
H-Index
2
About
Maurizio Pacilli is a leading researcher in surgical education and skill assessment, with a focus on urology training. His work centers on integrating artificial intelligence and simulation-based methods to transform how surgical competence is measured and taught. Pacilli’s most cited paper, “Surgical skill levels: Classification and analysis using deep neural network model and motion signals” (2019, 72 citations), pioneers the use of deep learning to objectively classify surgical proficiency from motion data, offering a data-driven alternative to subjective evaluation. His more recent work, “Simulation-based education in urology – an update” (2023, 18 citations), provides a comprehensive overview of how simulation-based education (SBE) has replaced traditional apprenticeship models over the past three decades, emphasizing its effectiveness in developing both technical and non-technical skills. Pacilli’s contributions are pivotal in advancing competency-based training, making surgical education more rigorous, measurable, and adaptable. His research has significant implications for improving patient safety and training efficiency, positioning him as a key figure in the modernization of surgical pedagogy.
Research Focus
Key Achievements
Top Papers
- 1
- 2Simulation-based education in urology – an update18 citations · 2023