Overcoming the challenges to implementation of artificial intelligence in pathology
Cet article passe en revue les développements de ces 10 dernières années en matière de pathologie numérique et computationnelle, identifie les défis à relever concernant l'implémentation de l'intelligence artificielle en pathologie et présente des moyens pour surmonter ces obstacles
Pathologists worldwide are facing remarkable challenges with the increasing workloads and the lack of time to provide consistently high-quality patient care. The application of artificial intelligence (AI) to digital whole slide images has the potential of democratizing the access to expert pathology and affordable biomarkers, by supporting pathologists in the provision of timely and accurate diagnosis as well as supporting oncologists by extracting prognostic and predictive biomarkers directly from tissue slides. The long-awaited adoption of AI in pathology, however, has not materialized, and the transformation of pathology is happening at a pace that is much slower than that observed in other fields (eg,, radiology). Here, we provide a critical summary of the developments in digital and computational pathology in the last ten years, outline key hurdles and ways to overcome them, and provide a perspective for AI-supported precision oncology in the future.
Journal of the National Cancer Institute , article en libre accès, 2022