BACKGROUND: The safety and efficiency of minimally invasive approaches for liver resection have been confirmed (Wakabayashi in Ann Surg, 2015). However, laparoscopy suffers from several limitations due to technical difficulties, particularly for diff...
BACKGROUND: Radiomics may provide more objective and accurate predictions for extrahepatic cholangiocarcinoma (ECC). In this study, we developed radiomics models based on magnetic resonance imaging (MRI) and machine learning to preoperatively predict...
Open surgery is the standard of care for perihilar cholangiocarcinoma (pCCA). With the aim of oncologic radicality, it requires a complex major hepatectomy with biliary reconstruction. The postoperative course is consequently often complicated, with ...
OBJECTIVES: To develop a proof-of-concept "interpretable" deep learning prototype that justifies aspects of its predictions from a pre-trained hepatic lesion classifier.
OBJECTIVES: To develop and validate a proof-of-concept convolutional neural network (CNN)-based deep learning system (DLS) that classifies common hepatic lesions on multi-phasic MRI.
BACKGROUND: Laparoscopic hepatectomy has been performed in many hospitals, with the development of the laparoscopic operation technique. However, performing complex laparoscopic hepatectomy, such as right hemihepatectomy, is still a challenge. The ai...
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