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Comparison of Pathways and Detection Strategies for Pancreatic Ductal Adenocarcinoma (PDAC) Using Genetically Engineered Mouse Model (GEMM)
(2022-04)
Pancreatic ductal adenocarcinoma (PDAC) is a deadly, invasive pancreatic cancer with 5-year survival for patients close to 7.1%. The difficulty of researching PDAC comes from a variety of factors that lead to its development, ...
A Deep Learning Model for Pancreatic Ductal Adenocarcinoma Chemotherapy Outcome Prediction
(2022-04)
Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive abdominal malignancy, with an overall 8.5% 5-year survival rate. PDAC is often detected too late for surgical resection and associated with resistance to chemotherapy ...
A Machine Learning Approach Towards Prediction of Pancreatic Cancer Using Gene Expression and DNA Methylation
(2024-04)
DNA methylation is a process that can affect gene accessibility and therefore gene expression. Methylation can affect genes that are associated with suppressing or contributing to tumor growth and progression. In this ...
Integrating U-Net and LLM Agents for Pancreatic Ductal Adenocarcinoma Diagnosis
(2025-04)
This study proposes an AI driven pipeline that combines, pancreas segmentation outcome for Pancreatic Ductal Adenocarcinoma (PDAC) diagnosis with a large language model (LLM) agent to enhance diagnostic and clinical analysis. ...
A Machine Learning Approach Towards Prediction of Pancreatic Cancer Using Gene Expression and DNA Methylation
(2025-04)
Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, accounting for over 90% of cases, and is characterized by aggressive growth, early metastasis, and resistance to therapy. A comprehensive ...