Artificial Intelligence-Based Opportunities in Liver Pathology-A Systematic Review.
Pierre AllaumeNoémie RabilloudBruno TurlinEdouard Bardou-JacquetOlivier LoréalJulien CalderaroZine-Eddine KheneOscar AcostaRenaud De CrevoisierNathalie Rioux-LeclercqThierry PecotSolène-Florence Kammerer-JacquetPublished in: Diagnostics (Basel, Switzerland) (2023)
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.