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Artificial Intelligence-Based Opportunities in Liver Pathology—A Systematic Review
22
Zitationen
12
Autoren
2023
Jahr
Abstract
DNN-based models are well represented in the field of liver pathology, and their applications are diverse. Most studies, however, presented at least one domain with a high risk of bias according to the QUADAS-2 tool. Hence, DNN models in liver pathology present future opportunities and persistent limitations. To our knowledge, this review is the first one solely focused on DNN-based applications in liver pathology, and to evaluate their bias through the lens of the QUADAS2 tool.
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Autoren
Institutionen
- Hôpital Pontchaillou(FR)
- Centre Hospitalier Universitaire de Rennes(FR)
- Laboratoire Traitement du Signal et de l'Image(FR)
- Inserm(FR)
- Assistance Publique – Hôpitaux de Paris(FR)
- Centre Eugène Marquis(FR)
- Structure Fédérative de Recherche en Biologie et Santé de Rennes(FR)
- Centre National de la Recherche Scientifique(FR)