Results 231 to 240 of about 1,696,620 (311)

Robotic Versus Laparoscopic Anatomic Liver Resection: Comparison of Perioperative Outcomes—A Systematic Review and Meta‐Analysis

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Minimally invasive anatomic liver resection (AR) including major hepatectomy and liver parenchyma‐sparing AR is technically complex and demanding. This systematic review with meta‐analysis including 15 studies comparing 2042 robotic AR and 2129 laparoscopic AR patients demonstrated largely comparable perioperative outcomes and partly better outcomes ...
Yutaro Kato   +3 more
wiley   +1 more source

Prognostic Significance of Portal Vein Tumor Thrombus in Pancreatic Ductal Adenocarcinoma Treated With Chemoradiotherapy

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim To examine the significance of portal vein tumor thrombus (PVTT) as a prognostic factor for patients with pancreatic ductal adenocarcinoma (PDAC) treated with chemoradiotherapy (CRT) followed by surgery. Methods The study retrospectively examined 313 patients with borderline resectable (BR) or locally advanced (LA) PDAC who underwent CRT ...
Aoi Hayasaki   +9 more
wiley   +1 more source

3D investigation and modeling of the geometric effects on porosity in packed beds

open access: yesAIChE Journal, EarlyView.
Abstract In porous beds, physical boundaries restrict particle arrangement, leading to inhomogeneous porosity. This paper reports on the porosity profiles that are the result of geometric effects on monodisperse packed beds in cylindrical and cubic arrangements. Special focus is given to the influence of edges and corners in cubic geometries.
Bastian Oldach   +3 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang   +4 more
wiley   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

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