AIMC Topic: Carcinoma, Pancreatic Ductal
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Deep Learning and Automatic Differentiation of Pancreatic Lesions in Endoscopic Ultrasound: A Transatlantic Study.
Clinical and translational gastroenterology
Nov 1, 2024
INTRODUCTION: Endoscopic ultrasound (EUS) allows for characterization and biopsy of pancreatic lesions. Pancreatic cystic neoplasms (PCN) include mucinous (M-PCN) and nonmucinous lesions (NM-PCN). Pancreatic ductal adenocarcinoma (P-DAC) is the commo...
Diagnosis of Pancreatic Ductal Adenocarcinoma Using Deep Learning.
Sensors (Basel, Switzerland)
Oct 31, 2024
Recent advances in artificial intelligence (AI) research, particularly in image processing technologies, have shown promising applications across various domains, including health care. There is a significant effort to use AI for the early diagnosis ...
Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.
BMC gastroenterology
Oct 31, 2024
BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and the integration of multiple models has further improved accuracy. In this study, we aimed to construct a combined prognostic model using deep learning-...
Advancements in early detection of pancreatic cancer: the role of artificial intelligence and novel imaging techniques.
Abdominal radiology (New York)
Oct 28, 2024
Early detection is crucial for improving survival rates of pancreatic ductal adenocarcinoma (PDA), yet current diagnostic methods can often fail at this stage. Recently, there has been significant interest in improving risk stratification and develop...
Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study.
Computational biology and chemistry
Oct 24, 2024
Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, and a notably low five-year survival rate, underscoring the critical need for early detection methods and more effective therapeutic approaches. This r...
A convolutional neural network-based system for identifying neuroendocrine neoplasms and multiple types of lesions in the pancreas using EUS (with videos).
Gastrointestinal endoscopy
Oct 17, 2024
BACKGROUND AND AIMS: EUS is sensitive in detecting pancreatic neuroendocrine neoplasm (pNEN). However, the endoscopic diagnosis of pNEN is operator-dependent and time-consuming because pNEN mimics normal pancreas and other pancreatic lesions. We inte...
A time-dependent explainable radiomic analysis from the multi-omic cohort of CPTAC-Pancreatic Ductal Adenocarcinoma.
Computer methods and programs in biomedicine
Sep 7, 2024
BACKGROUND AND OBJECTIVE: In Pancreatic Ductal Adenocarcinoma (PDA), multi-omic models are emerging to answer unmet clinical needs to derive novel quantitative prognostic factors. We realized a pipeline that relies on survival machine-learning (SML) ...
Data privacy-aware machine learning approach in pancreatic cancer diagnosis.
BMC medical informatics and decision making
Sep 5, 2024
PROBLEM: Pancreatic ductal adenocarcinoma (PDAC) is considered a highly lethal cancer due to its advanced stage diagnosis. The five-year survival rate after diagnosis is less than 10%. However, if diagnosed early, the five-year survival rate can reac...
Development of a Diagnostic Model for Pancreatic Ductal Adenocarcinoma Using Machine Learning and Blood-Based miRNAs.
Oncology
Sep 4, 2024
INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate among all major cancers due to a lack of symptoms in early stages, early detection tools, and optimal therapies for late-stage patients. Thus, effective and non-invasi...
A Deep Learning Approach for the Identification of the Molecular Subtypes of Pancreatic Ductal Adenocarcinoma Based on Whole Slide Pathology Images.
The American journal of pathology
Aug 31, 2024
Delayed diagnosis and treatment resistance result in high pancreatic ductal adenocarcinoma (PDAC) mortality rates. Identifying molecular subtypes can improve treatment, but current methods are costly and time-consuming. In this study, deep learning m...
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