Results 221 to 230 of about 517,382 (360)

Prognostic Impact of Immunoscore in Pathological Stage III Differentiated Gastric Cancer: A Multicenter Cohort Study Including PD‐L1/PD‐L2 Expression Analysis

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
We assessed the prognostic ability of the Immunoscore and PD‐L1 or PD‐L2 expression in pStage III GC patients by immunohistochemistry. The results showed that Immunoscore was an independent prognostic factor in differentiated GC, but not in undifferentiated GC.
Yoshiro Yukawa   +13 more
wiley   +1 more source

Subjective and Objective Quality Assessment of Transparently Encrypted JPEG2000 Images

open access: green, 2010
Thomas Stütz   +4 more
openalex   +1 more source

Association Between Liver Function Grade and Post‐Hepatectomy Liver Failure in Patients With Hepatocellular Carcinoma: A Latent Class Analysis

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
We retrospectively analyzed clinical data from patients who underwent hepatectomy for hepatocellular carcinoma (HCC) using LCA‐based grading system. These findings provide a new risk stratification framework for the design of precision surgery to treat patients with HCC.
Ling Liu   +5 more
wiley   +1 more source

Transient modeling of extraction columns: Parameter estimation, uncertainty analysis, and operation optimization

open access: yesAIChE Journal, EarlyView.
Abstract Despite extensive modeling efforts in extraction research, transient column models are rarely applied in industry due to concerns regarding parameter identifiability and model reliability. To address this, we analyzed uncertainty propagation from estimated parameters in a previously introduced column model and assessed identifiability via ill ...
Andreas Palmtag   +2 more
wiley   +1 more source

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

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