L’intelligenza Artificiale nei processi di Anatomia Patologica:: Una gestione Lean per l’implementazione delle tecnologie
Year: 2026
Type: article
Abstract: Background: Pathology is undergoing a radical transformation driven by the introduction of Artificial Intelligence (AI) and Digital Pathology (DP). The introduction of AI in Pathology represents one of the main directions of innovation in modern diagnostics. Digital Pathology, machine learning, and deep learning algorithms enable automated analysis of histological images, with potential benefits in terms of diagnostic accuracy, reduced interobserver variability, and operational efficiency. However, the implementation of AI poses significant technological, organizational, economic, and ethical/regulatory challenges. This paper analyzes the main applications of AI in Anatomical Pathology, discussing its limitations and sustainability implications, and proposes an implementation model based on Lean principles for workflow redesign and change management, aimed at ensuring clinical value, process control, and appropriate use of technology. The goal is not simply to digitize existing analog processes, but to optimize them to ensure traceability, diagnostic accuracy, and long-term sustainability. Methods: This narrative review analyzes current AI applications in anatomical pathology, focusing on diagnostic support, workflow integration, and sustainability. A Lean Healthcare perspective is adopted to evaluate process redesign, change management, and value generation for patients and healthcare organizations. Results: AI applications, particularly deep learning models applied to whole-slide images, improve diagnostic reproducibility and efficiency, especially in oncology. However, implementation requires significant investments in digital infrastructure, data governance, validation, and staff training. Lean-based process analysis supports the adoption of appropriate technologies and mitigates the risks of inefficiency and organizational resistance. Conclusion: Artificial intelligence represents a strategic opportunity for anatomical pathology, provided its adoption is guided by structured process analysis, healthcare technology assessment, and lean management principles. Sustainable implementation depends on a balance between technological innovation, clinical value, organizational preparedness, and patient-centered outcomes.
Author: Virgili, Roberto
Language: Italian
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7214822546