AIMC Topic: Hepatectomy

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Robotic major and minor hepatectomy: critical appraisal of learning curve and its impact on outcomes.

Surgical endoscopy
BACKGROUND: Robotic hepatectomy has gained increasing acceptance across the US. Although the robotic approach offers significant technical advantages, it is still bound by the individual surgeon's learning curve. Proficiency in this approach should t...

[Robotic Left Hepatectomy Using the Glissonean Pedicle Approach for the Treatment of Caroli's Syndrome].

Zentralblatt fur Chirurgie
BACKGROUND: Caroli's syndrome is a rare disease characterised by non-obstructive dilation of intrahepatic bile ducts, hepatic fibrosis, and an increased risk of developing cholangiocarcinoma. Minimally invasive liver resection has recently been incre...

Artificial intelligence for identification of focal lesions in intraoperative liver ultrasonography.

Langenbeck's archives of surgery
PURPOSE: Intraoperative ultrasonography (IOUS) of the liver is a crucial adjunct in every liver resection and may significantly impact intraoperative surgical decisions. However, IOUS is highly operator dependent and has a steep learning curve. We de...

Automated surgical workflow identification by artificial intelligence in laparoscopic hepatectomy: Experimental research.

International journal of surgery (London, England)
BACKGROUND: To perform accurate laparoscopic hepatectomy (LH) without injury, novel intraoperative systems of computer-assisted surgery (CAS) for LH are expected. Automated surgical workflow identification is a key component for developing CAS system...

A deep learning model with incorporation of microvascular invasion area as a factor in predicting prognosis of hepatocellular carcinoma after R0 hepatectomy.

Hepatology international
INTRODUCTION: Microvascular invasion (MVI) is a known risk factor for prognosis after R0 liver resection for hepatocellular carcinoma (HCC). The aim of this study was to develop a deep learning prognostic prediction model by incorporating a new facto...