Pancreatic Diseases

Machine-Learning-Driven Discovery of -Phenylbenzenesulfonamides as a Novel Chemotype for Lactate Dehydrogenase A Inhibition with Anti-Pancreatic Cancer Activity.

Lactate dehydrogenase A (LDHA) is a promising target for cancer therapy due to its crucial role in aerobic glycolysis. Despite extensive efforts, the structural diversity of LDHA inhibitors remains limited. Here, we utilized machine learning techniques, particularly reinforcement learning models, along with molecular dynamics simulations and biological validation, to identify -phenylbenzenesulfona...

Data Extraction and Curation from Radiology Reports for Pancreatic Cyst Surveillance Using Large Language Models.

INTRODUCTION: Manual curation of radiographic features in pancreatic cyst registries for data abstraction and longitudinal evaluation is time consuming and limits widespread implementation. We examined the feasibility and accuracy of using large language models (LLMs) to extract clinical variables from radiology reports.

MRI sequence focused on pancreatic morphology evaluation: three-shot turbo spin-echo with deep learning-based reconstruction.

BackgroundHigher-resolution magnetic resonance imaging sequences are needed for the early detection of pancreatic cancer.PurposeTo compare the quality...

Radiomics in Early Detection of Pancreatic Ductal Adenocarcinoma: A Close Look at Its Current Status and Challenges to Clinical Implementation.

Radiomics is a mathematical approach to medical images to extract quantitative features generating a "radiomics signature." The radiomics workflow inv...

Machine learning-based prediction model for post-ERCP cholangitis in patients with malignant biliary obstruction: a retrospective multicenter study.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is the preferred palliative treatment for patients with unresectable malignant bilia...

Multicenter validation of a cholangioscopy artificial intelligence for evaluation of biliary tract disease.

INTRODUCTION: Clinicians struggle to accurately classify biliary strictures as benign or malignant. Current ERCP-based sampling modalities including b...

A CT-Based Deep Learning Radiomics Nomogram for Early Recurrence Prediction in Pancreatic Cancer: A Multicenter Study.

BACKGROUND: Early recurrence (ER) following curative-intent surgery remains a major obstacle to improving long-term outcomes in patients with pancreat...

Identification and verification of feature biomarkers associated with CD14 monocytes in type 1 diabetes.

AIMS/INTRODUCTION: Monocytes contribute to the immune dysregulation of pancreatic islets in Type 1 diabetes mellitus (T1D). This study aims to identif...

Targeting PFKFB3 to restore glucose metabolism in acute pancreatitis via nanovesicle delivery.

BACKGROUND: Acute pancreatitis (AP) is a severe inflammatory disease frequently accompanied by disturbances in glucose metabolism, which further compl...

Multi-omics integration and machine learning uncover molecular basal-like subtype of pancreatic cancer and implicate A2ML1 in promoting tumor epithelial-mesenchymal transition.

BACKGROUND: Pancreatic cancer (PC) represents a highly heterogeneous malignancy with poor prognosis, where precise molecular subtyping facilitates com...

Classification of Japanese type 1 diabetes based on clinical phenotypes and its association with diabetic complications: Across-sectional study.

INTRODUCTION: Despite the increasing number of studies using machine learning to develop individualized treatment strategies, only a few have been con...

Diagnostic performance of artificial intelligence based on contrast-enhanced computed tomography in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis.

PURPOSE: This meta-analysis systematically evaluated the diagnostic performance of artificial intelligence (AI) based on contrast-enhanced computed to...

Harnessing artificial intelligence for detection of pancreatic cancer: a machine learning approach.

PURPOSE: Pancreatic cancer (PC) is one of the most lethal malignancies, often presenting with nonspecific symptoms and a dismal prognosis. Despite adv...

Unveiling the mechanisms and promising molecular targets of curcumin in pancreatic cancer through multi-dimensional data.

Pancreatic cancer (PC) is a highly aggressive and fatal malignancy, primarily affecting older males. Curcumin, a potential anti-cancer agent, has been...

Impact of tertiary lymphoid structure-associated biomarkers on pancreatic cancer via a dual-disease analysis of psoriasis and pancreatic cancer.

Pancreatic cancer (PC), often referred to as the "king of cancers", has demonstrated limited success with immunotherapies, many of which are still und...

A predictive model for electrospun based Polyvinyl alcohol (PVA) nanofibers diameter using an artificial neural network.

The aim of this work is to develop a predictive model for electrospun based polyvinyl alcohol (PVA) nanofiber diameter. Artificial Neural Network is e...

Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions.

Road traffic accidents (RTAs) in Northwest Ethiopia, a region with a fatality rate of 32.2 per 100,000 residents, pose a critical public health challe...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elev...

An explainable multi-task deep learning framework for crash severity prediction using multi-source data.

Traffic accidents pose significant global challenges, causing substantial injuries, fatalities, and economic losses. Current research predominantly fo...

An interpretable machine learning model for predicting early liver metastasis after pancreatic cancer surgery.

BACKGROUND: Liver metastasis is the most frequent site of distant metastasis in pancreatic ductal adenocarcinoma (PDAC), significantly contributing to...