+ HEALTH Rationale and objectives To propose a new imaging biomarker, the pulmonary artery-to-vein volume difference (…± HEALTH Rationale and objectives The international application of artificial intelligence (AI) for lesion detection b…± HEALTH Rationale and objectives To address the challenge of preoperative prediction of synchronous liver metastasis…± HEALTH Objectives To conduct a nationwide survey among professionals working in oncology departments in China to inv…+ HEALTH The utilization of deep convolutional neural networks for the purpose of diagnosing diseases in the skin area…± HEALTH BACKGROUND . Gadolinium-based contrast agents remain essential for MRI but carry risks. Deep learning (DL) me…+ SCIENCE Gas Chromatography is a versatile separation technique widely used in analytical chemistry for constituent de…+ HEALTH Background Intracardiac echocardiography (ICE) facilitates left atrial (LA) reconstruction during atrial fibr…
TruaceTracing the truth around AIThursday, August 27, 2026
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TRV-2026-0907Certified recordPeer-reviewed

Predicting Synchronous Liver Metastasis in Pancreatic Cancer Using CT Radiomics and Clinical Features: A Machine Learning Approach

Rationale and objectives To address the challenge of preoperative prediction of synchronous liver metastasis (LM) in pancreatic cancer (PC), we developed and validated machine learning models integrating clinical and computed tomography (CT) radiomics features, and compared the performance and interpretability of linear (linear discriminant analysis [LDA]) versus nonlinear (multilayer perceptron [MLP]) architectures. Materials and methods This retrospective study enrolled 340 patients with pancreatic ductal aden…

Health · The Trace — both readings · certified 2026-08-27 · v1 · article view · machine-readable

Current reading — gain

Integrated machine learning models using CT radiomics and clinical predictors achieved accurate preoperative prediction of synchronous liver metastasis in pancreatic ductal adenocarcinoma in validation, intended to assist decisions on surveillance versus biopsy or neoadjuvant therapy for indeterminate subcentimeter CT-

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The linear LDA model showed unstable performance and poor discrimination in lymph-node-negative and pancreatic head tumor subgroups despite overall validation AUC.

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Truvace Impact Record TRV-2026-0907, v1: “Predicting Synchronous Liver Metastasis in Pancreatic Cancer Using CT Radiomics and Clinical Features: A Machine Learning Approach.” Truvace, 2026-08-27. /record/TRV-2026-0907 (accessed at citation time). sha256 282f0df419b2cdd3…

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