PURPOSE: Cholangiocyte phenotype hepatocellular carcinoma (HCC) is highly invasive. This study aims to develop and validate an optimal machine learning model to predict cholangiocyte phenotype HCC based on T1 mapping gadoxetic acid-enhanced MRI and t...
BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasively predicting high-grade patterns (HGPs) of invasive lung adenocarcinoma (LUAD).
BACKGROUND: Persistent sepsis-associated acute kidney injury (SA-AKI) shows poor clinical outcomes and remains a therapeutic challenge for clinicians. Early identification and prediction of persistent SA-AKI are crucial.
PurposeThis study investigated the applicability of a validated AI-algorithm for analyzing different retinal biomarkers in eyes affected by epiretinal membranes (ERMs) before and after surgery.MethodsA retrospective study included 40 patients surgica...
Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (TRD). Leveraging electronic medical records (EMR), this retrospective cohort study applied supervise...
PURPOSE: To establish and validate a model based on deep learning (DL), integrating radiomic features with relevant clinical features to generate nomogram, for predicting preoperative serosal invasion in gastric cancer (GC).
International journal of medical informatics
Apr 26, 2025
BACKGROUND: The aging population is driving increased healthcare demands and costs, prompting the need for effective home healthcare programs. Accurate patient assessment is essential for optimizing resource allocation and tailoring services.
PURPOSE: This study aimed to evaluate the efficacy of deep learning-based reconstruction (DLR) in improving pancreatic diffusion-weighted imaging (DWI) quality.
INTRODUCTION: About 25% of patients undergoing pancreaticoduodenectomy (PD) for right-sided pancreatic ductal adenocarcinoma (PDAC) die within 1 y of diagnosis. These patients carry all the risks of significant morbidity with no survival advantage wh...
European journal of nuclear medicine and molecular imaging
Apr 25, 2025
PURPOSE: To assess feasibility of lung cancer screening, we analysed lung lesion detectability simulating low-dose and convolutional neural network (CNN) denoised [F]-FDG PET/CT reconstructions.
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