Blood cancer prediction model based on deep learning technique.

Blood cancer is among the critical health concerns among people around the world and normally emanates from genetic and environmental issues. Early detection becomes essential, as the rate of death associated with it is high, to ensure that the rate of treatment success is up, and mortality reduced. This paper focuses on improving blood cancer diagnosis using advanced deep learning techniques like ResNetRS50, RegNetX016, AlexNet, Convnext, EfficientNet, Inception_V3, Xception, and VGG19.

Navigating complex arterial reconstruction in living donor liver transplantation: the role of the splenic artery as a viable conduit.

Background: In living donor liver transplantation (LDLT), maintaining hepatic arterial flow is critical for graft survival. Alternative methods are required when the recipient's hepatic artery is unsuitable due to extensive dissection or inadequate flow. This study evaluates the efficacy and safety of splenic artery transposition (SAT) for hepatic arterial reconstruction in LDLT.

Pancreaticoduodenectomy with pancreaticogastrostomy and an external pancreatic stent in risky patients: a propensity score-matched analysis.

Background: There is an ongoing debate about the most appropriate method for reconstructing the pancreas after a pancreaticoduodenectomy (PD). This study assessed the impact of pancreaticogastrostomy (PG) with an external pancreatic stent on postoperative outcomes following PD in high-risk patients.

Patients And Methods: This study involves a propensity score-matched analysis of high-risk patients who underwent PD with PG reconstruction.

Liver resection for hepatocellular carcinoma in elderly patients: does age matter?

Background: Evaluation of the influence of the age of the patients upon the outcomes of liver resection (LR) for hepatocellular carcinoma (HCC).

Methods: HCC patients who underwent LR between 2010 and 2020 were analyzed. They were divided into 3 groups depending on the patient's age.