customizable digital microscopy analysis platform (Visiopharm AS)
90
Structured Review
Visiopharm AS
customizable digital microscopy analysis platform
Customizable Digital Microscopy Analysis Platform, supplied by Visiopharm AS, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/customised+microscope/customizable+digital+microscopy+analysis+platform/pmc06697165-293-1-6
Average 90 stars, based on 1 article reviews
Customizable Digital Microscopy Analysis Platform, supplied by Visiopharm AS, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/customised+microscope/customizable+digital+microscopy+analysis+platform/pmc06697165-293-1-6
Average 90 stars, based on 1 article reviews
customizable digital microscopy analysis platform - by Bioz Stars,
2026-09
90/100 stars
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Microscopy:Article Title: Telencephalic outputs from the medial entorhinal cortex are copied directly to the hippocampus Article Snippet: .. The borders of CA1 were drawn on brain section images using a Article Title: Contrast-enhanced computed tomography radiomics and multilayer perceptron network classifier: an approach for predicting CD20 + B cells in patients with pancreatic ductal adenocarcinoma. Article Snippet: Purpose To develop and validate a machine-learning classifier based on contrast-enhanced computed tomography (CT) for the preoperative prediction of CD20+ B lymphocyte expression in patients with pancreatic ductal adenocarcinoma (PDAC).. Methods Overall, 189 patients with PDAC (n = 132 and n = 57 in the training and validation sets, respectively) underwent immunohistochemistry and radiomics feature extraction.. The X-tile software was used to stratify them into groups with ‘high’ and ‘low’ CD20+ B lymphocyte expression levels. Article Title: Preoperative Radiomics Approach to Evaluating Tumor-Infiltrating CD8 + T Cells in Patients With Pancreatic Ductal Adenocarcinoma Using Noncontrast Magnetic Resonance Imaging. Article Snippet: Background: CD8T cell in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment response of patients.. Accurate preoperative CD8 T-cell expression can better identify the population benefitting from immunotherapy.. Purpose: To develop and validate a machine learning classifier based on noncontrast magnetic resonance imaging (MRI) for the preoperative prediction of CD8 T-cell expression in patients with PDAC. Article Title: CT radiomics signature: a potential biomarker for fibroblast activation protein expression in patients with pancreatic ductal adenocarcinoma. Article Snippet: Purpose To develop and validate a radiomics model to predict fibroblast activation protein (FAP) expression in patients with pancreatic ductal adenocarcinoma (PDAC).. Methods This retrospective study included consecutive 152 patients with PDAC who underwent MDCT scan and surgical resection from January 2017 to December 2017 (training set) and from January 2018 to April 2018 (validation set).. In the training set, 1409 portal radiomic features were extracted from each patient’s preoperative imaging. Article Title: Telencephalic outputs from the medial entorhinal cortex are copied directly to the hippocampus Article Snippet: .. The borders of CA1 were drawn on brain section images using a Article Title: Noncontrast Magnetic Resonance Radiomics and Multilayer Perceptron Network Classifier: An approach for Predicting Fibroblast Activation Protein Expression in Patients With Pancreatic Ductal Adenocarcinoma. Article Snippet: Background: Fibroblast activation protein (FAP) in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment of patients.. Accurate preoperative FAP expression can better identify the population benefitting from FAP-targeting drugs.. Purpose: To develop and validate a machine learning classifier based on noncontrast MRI for the preoperative prediction of FAP expression in patients with PDAC. Article Title: Machine learning for MRI radiomics: a study predicting tumor-infiltrating lymphocytes in patients with pancreatic ductal adenocarcinoma. Article Snippet: Objective To develop and validate a machine learning classifier based on magnetic resonance imaging (MRI), for the preoperative prediction of tumor-infiltrating lymphocytes (TILs) in patients with pancreatic ductal adenocarcinoma (PDAC).. Materials and methods In this retrospective study, 156 patients with PDAC underwent MR scan and surgical resection.. The expression of CD4, CD8 and CD20 was detected and quantified using immunohistochemistry, and TILs score was achieved by Cox regression model. All patients were divided into TILs score-low and TILs score-high groups. Expressing:Article Title: Contrast-enhanced computed tomography radiomics and multilayer perceptron network classifier: an approach for predicting CD20 + B cells in patients with pancreatic ductal adenocarcinoma. Article Snippet: Purpose To develop and validate a machine-learning classifier based on contrast-enhanced computed tomography (CT) for the preoperative prediction of CD20+ B lymphocyte expression in patients with pancreatic ductal adenocarcinoma (PDAC).. Methods Overall, 189 patients with PDAC (n = 132 and n = 57 in the training and validation sets, respectively) underwent immunohistochemistry and radiomics feature extraction.. The X-tile software was used to stratify them into groups with ‘high’ and ‘low’ CD20+ B lymphocyte expression levels. Article Title: Noncontrast Magnetic Resonance Radiomics and Multilayer Perceptron Network Classifier: An approach for Predicting Fibroblast Activation Protein Expression in Patients With Pancreatic Ductal Adenocarcinoma. Article Snippet: Background: Fibroblast activation protein (FAP) in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment of patients.. Accurate preoperative FAP expression can better identify the population benefitting from FAP-targeting drugs.. Purpose: To develop and validate a machine learning classifier based on noncontrast MRI for the preoperative prediction of FAP expression in patients with PDAC. Article Title: Prediction of Tumor-Infiltrating CD20 + B-Cells in Patients with Pancreatic Ductal Adenocarcinoma Using a Multilayer Perceptron Network Classifier Based on Non-contrast MRI. Article Snippet: © A ht Rationale and Objectives: Conventional chemotherapy has limited benefit in pancreatic ductal adenocarcinoma (PDAC), necessitating identification of novel therapeutic targets.. Radiomics may enable non-invasive prediction of CD20 expression, a hypothesized therapeutic target in PDAC.. To develop a machine learning classifier based on noncontrast magnetic resonance imaging for predicting CD20 expression in PDAC. |