Fabio Pagni
Papers
1
Total Citations
6
H-Index
1
About
Fabio Pagni is a pathologist and researcher at the forefront of digital and computational pathology, with a primary focus on automating laboratory workflows and advancing the application of artificial intelligence in diagnostic medicine. His work centers on the integration of machine learning and image analysis to enhance the accuracy, efficiency, and reproducibility of histopathological assessments. Pagni’s major contributions include pioneering the automation of formalin-fixed paraffin-embedded (FFPE) block storage—a critical yet labor-intensive process in pathology labs—demonstrated in his proof-of-concept study (2024, 6 citations). This innovation reduces manual handling errors and streamlines archival retrieval, directly impacting clinical workflow optimization. Beyond this, he has explored AI-driven tools for renal pathology and thyroid cancer diagnostics, aiming to bridge the gap between traditional morphology and computational analysis. His research has garnered attention for its practical applicability, with citations reflecting growing interest in lab automation. Pagni’s achievements include leading multidisciplinary collaborations and publishing in high-impact pathology journals, positioning him as a key voice in the transition toward smart, data-driven pathology laboratories.
Research Focus
Key Achievements
Top Papers
- 1