AIMC Topic: Pancreatic Neoplasms

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Deep causal learning for pancreatic cancer segmentation in CT sequences.

Neural networks : the official journal of the International Neural Network Society
Segmenting the irregular pancreas and inconspicuous tumor simultaneously is an essential but challenging step in diagnosing pancreatic cancer. Current deep-learning (DL) methods usually segment the pancreas or tumor independently using mixed image fe...

Identification of pancreatic cancer risk factors from clinical notes using natural language processing.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of ris...

A causality-inspired generalized model for automated pancreatic cancer diagnosis.

Medical image analysis
Pancreatic cancer (PC) is a severely malignant cancer variant with high mortality. Since PC has no obvious symptoms, most PC patients are belatedly diagnosed at advanced disease stages. Recently, artificial intelligence (AI) approaches have demonstra...

Continuing Medical Education Questions: August 2024.

The American journal of gastroenterology
Article Title: Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review and Assessment.

Machine Learning Developed a MYC Expression Feature-Based Signature for Predicting Prognosis and Chemoresistance in Pancreatic Adenocarcinoma.

Biochemical genetics
MYC has been identified to profoundly influence a wide range of pathologic processes in cancers. However, the prognostic value of MYC-related genes in pancreatic adenocarcinoma (PAAD) remains unclarified. Gene expression data and clinical information...