Deep learning and radiomics with medical imaging have demonstrated strong potential to
improve diagnostic accuracy of pancreatic cancer, facilitate personalized treatment …

Artificial intelligence (AI) has experienced substantial progress over the last ten years in
many fields of application, including healthcare. In hepatology and pancreatology, major …

Background A priori identification of patients at risk of artificial intelligence (AI) failure in
diagnosing cancer would contribute to the safer clinical integration of diagnostic algorithms …

Background Deep learning (DL) may facilitate the diagnosis of various pancreatic lesions at
imaging. Purpose To develop and validate a DL-based approach for automatic identification …

Background & Aims The aims of our case-control study were (1) to develop an automated 3-
dimensional (3D) Convolutional Neural Network (CNN) for detection of pancreatic ductal …

Simple Summary Tumor segmentation is a key step in oncologic imaging processing and is
a time-consuming process usually performed manually by radiologists. To facilitate it, there …

Artificial Intelligence and its sub-branches like MachineLearning (ML) and Deep Learning
(DL) applications have the potential to have positive effects that can directly affect human …

In the current era of machine learning and radiomics, one of the challenges is the automatic
segmentation of organs and tumors. Tumor detection is mostly based on a radiologist's …

Pancreatic cancer (PC) has a low incidence rate but a high mortality, with patients often in
the advanced stage of the disease at the time of the first diagnosis. If detected, early …

Simple Summary In computer-assisted diagnostics for pancreatic cancer, attributes featuring
irregular contours and indistinct boundaries on CT images present challenges in acquiring …