AIMC Topic: Liver Transplantation
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Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study.
Hepatology international
Mar 29, 2022
BACKGROUND: There is a growing need for new improved classifiers of prognosis in hepatocellular carcinoma (HCC) patients to stratify them effectively.
Splenic artery steal syndrome in patients with orthotopic liver transplant: Where to embolize the splenic artery?
PloS one
Mar 10, 2022
PURPOSE: This study compared proximal and distal embolization of the splenic artery (SA) in patients with splenic artery steal syndrome (SAS) after orthotopic liver transplantation (OLT) regarding post interventional changes of liver function to iden...
Laparoscopic donor and recipient hepatectomy followed by robot-assisted liver graft implantation in living donor liver transplantation.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Jan 11, 2022
Minimally invasive surgery has been introduced for liver transplantations. Although laparoscopic or robot-assisted living donor hepatectomy is being used, minimally invasive surgery is rarely performed in recipients during liver transplantation. A 63...
Robotic donor hepatectomy: A major breakthrough in living donor liver transplantation.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Dec 6, 2021
Living donation in many countries is the main resource of organs. Healthy, volunteering individuals deserve the highest safety standards possible in addition to the least invasive technique to procure the organs. Since the introduction of living dono...
Artificial Intelligence in Liver Transplantation.
Transplantation proceedings
Nov 2, 2021
BACKGROUND: Advancements based on artificial intelligence have emerged in all areas of medicine. Many decisions in organ transplantation can now potentially be addressed in a more precise manner with the aid of artificial intelligence.
Statistical methods versus machine learning techniques for donor-recipient matching in liver transplantation.
PloS one
May 21, 2021
Donor-Recipient (D-R) matching is one of the main challenges to be fulfilled nowadays. Due to the increasing number of recipients and the small amount of donors in liver transplantation, the allocation method is crucial. In this paper, to establish a...
Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data.
The Lancet. Digital health
Apr 12, 2021
BACKGROUND: Survival of liver transplant recipients beyond 1 year since transplantation is compromised by an increased risk of cancer, cardiovascular events, infection, and graft failure. Few clinical tools are available to identify patients at risk ...
Development and performance assessment of novel machine learning models to predict pneumonia after liver transplantation.
Respiratory research
Mar 31, 2021
BACKGROUND: Pneumonia is the most frequently encountered postoperative pulmonary complications (PPC) after orthotopic liver transplantation (OLT), which cause high morbidity and mortality rates. We aimed to develop a model to predict postoperative pn...
An imageomics and multi-network based deep learning model for risk assessment of liver transplantation for hepatocellular cancer.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 11, 2021
INTRODUCTION: Liver transplantation (LT) is an effective treatment for hepatocellular carcinoma (HCC), the most common type of primary liver cancer. Patients with small HCC (<5 cm) are given priority over others for transplantation due to clinical al...
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