Latest AI and machine learning research in pancreatic diseases for healthcare professionals.
A novel 3D nnU-Net-based of algorithm was developed for fully-automated multi-organ segmentation in abdominal CT, applicable to both non-contrast and post-contrast images. The algorithm was trained using dual-energy CT (DECT)-obtained portal venous phase (PVP) and spatiotemporally-matched virtual non-contrast images, and tested using a single-energy (SE) CT dataset comprising PVP and true non-cont...
This study was undertaken to observe the effect of body mass index (BMI) on perioperative outcomes and survival when comparing robotic vs 'open' pancreaticoduodenectomy. With IRB approval, we prospectively followed 505 consecutive patients who underwent either robotic or 'open' pancreaticoduodenectomy from 2012 to 2021. For illustrative purposes, patients were separated based on the Center for Dis...
RATIONALE AND OBJECTIVES: To develop and validate a deep learning (DL)-based method for pancreas segmentation on CT and automatic measurement of pancr...
BACKGROUND: Although the current trend in pancreatoduodenectomy (PD) has shifted from open surgery to minimally invasive surgery (MIS), evidence on th...
MYC has been identified to profoundly influence a wide range of pathologic processes in cancers. However, the prognostic value of MYC-related genes in...
OBJECTIVE: Aim to establish a multimodal model for predicting severe acute pancreatitis (SAP) using machine learning (ML) and deep learning (DL).
In the setting of pronounced inflammation, changes in the epithelium may overlap with neoplasia, often rendering it impossible to establish a diagnosi...
Severe acute pancreatitis (SAP) is a life-threatening gastrointestinal emergency. The study aimed to identify biomarkers and investigate molecular mec...
Accurate segmentation of the pancreas from abdominal computed tomography (CT) images is challenging but essential for the diagnosis and treatment of p...
This research leverages a novel deep learning model, Inception-v3, to predict pedestrian crash severity using data collected over five years (2016-202...
This study aimed to assess the antioxidant, enzyme inhibitory, physicochemical and sensory properties of instant bio-yoghurts containing multi-purpose...
BACKGROUND: Identifying co-occurring mental disorders and elevated risk is vital for optimization of healthcare processes. In this study, we will use ...
BACKGROUND: Despite the prognostic relevance of cachexia in pancreatic cancer, individual body composition has not been routinely integrated into trea...
BACKGROUND: Brain metastases (BM) are rare in pancreatic ductal adenocarcinoma (PDAC) and little data exists concerning these patients and their outco...
BACKGROUND: Predictive eHealth tools will change the field of medicine, however long-term data is scarce. Here, we report findings on data collected o...
BACKGROUND: Robotic pancreaticoduodenectomy (RPD) is technically demanding, and 20-50 cases are required to surpass the learning curve. This study aim...
We focused on assessing the antimicrobial effects of functional yoghurts supplemented with clove and probiotics. The formulation of aqueous clove extr...
Background Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer (PC) in the United States. In patients with resectable...
The effects of coffee ( L.) berry pulp extracts (CBP extracts) on the improvement of diabetes, obesity, and non-alcoholic fatty liver disease (NAFLD) ...
Polychlorinated biphenyls (PCBs) are persistent organic pollutants and endocrine disruptors that have been implicated in potential damage to human sem...