Pancreatic Diseases

Deep-learning based automated pancreas segmentation on CT scans of chronic pancreatitis patients.

OBJECTIVES: This study aimed to develop an artificial intelligence (AI)-based segmentation model for accurate delineation of the complex pancreas in patients with chronic pancreatitis (CP) using computer tomography (CT) scans obtained during routine clinical work-up. Validation was performed with internal and external test datasets. A secondary objective was to evaluate the impact of visceral fat ...

Fluorescent Microneedle Sensors Based on Tb@Hydrogen-Bonded Organic Frameworks for Real-Time Food Freshness Monitoring.

As crucial biomarkers of food spoilage, portable and real-time monitoring of the biogenic amines (BAs) is essential to ensuring food safety. In light of this, a ratiometric fluorescent probe (Tb@HOF-BPTC) is developed, which exhibits distinct fluorescence response upon exposure to BAs. It demonstrates exceptional analytical performance with a low limit of detection ranging from 3.1 to 14.3 μM and ...

Serum-Based Detection of Pancreatic and Ovarian Cancer via a Nanoparticle-Enhanced Fluorescence Array and Machine Learning.

: Early detection of oncological diseases such as pancreatic ductal adenocarcinoma (PDAC) and ovarian cancer (OV) is pivotal for successful treatment ...

Label-free single-cell phenotyping to determine tumor cell heterogeneity in pancreatic cancer in real time.

Resistance to chemotherapy of pancreatic ductal adenocarcinoma (PDAC) is largely driven by intratumoral heterogeneity (ITH) due to tumor cell plastici...

Improving Social Determinants of Health Documentation in French EHRs Using Large Language Models

Social determinants of health (SDoH) significantly influence health outcomes, shaping disease progression, treatment adherence, and health dispariti...

PanTS: The Pancreatic Tumor Segmentation Dataset

PanTS is a large-scale, multi-institutional dataset curated to advance research in pancreatic CT analysis. It contains 36,390 CT scans from 145 medi...

Medical management of pancreatic cancer: from personalization to broadening treatment strategies.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most heterogeneous and deadly cancers. This review examines recently implemented strategies to i...

Integrating AI/ML and multi-omics approaches to investigate the role of TNFRSF10A/TRAILR1 and its potential targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival of under 10 % despite current therapies...

Advances in pancreatic cancer diagnosis: from DNA methylation to AI-assisted imaging.

INTRODUCTION: Pancreatic Cancer (PC) is a highly aggressive tumor that is mainly diagnosed at later stages. Various imaging technologies, such as CT, ...

Pancreas segmentation in CT scans: A novel MOMUNet based workflow.

Automatic pancreas segmentation in CT scans is crucial for various medical applications, including early diagnosis and computer-assisted surgery. Howe...

Augmenting Common Spatial Patterns to deep learning networks for improved alcoholism detection using EEG signals.

One of the main risk factors for numerous health problems is excessive drinking. Alcoholism is a severe disorder that can affect a person's thinking a...

LUNETR: Language-Infused UNETR for precise pancreatic tumor segmentation in 3D medical image.

The identification of early micro-lesions and adjacent blood vessels in CT scans plays a pivotal role in the clinical diagnosis of pancreatic cancer, ...

From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction.

Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therap...

Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: In Pancreatic Ductal Adenocarcinoma (PDAC), current prognostic scores are unable to fully capture the biological heterogeneity of the dise...

Development and preliminary testing of a secure large language model-based chatbot for brief alcohol counseling in young adults.

OBJECTIVE: Young adults face elevated risks from alcohol use yet encounter significant barriers to accessing evidence-based interventions. Large langu...

Computationally Enabled Polychromatic Polarized Imaging Enables Mapping of Matrix Architectures that Promote Pancreatic Ductal Adenocarcinoma Dissemination.

Pancreatic ductal adenocarcinoma (PDA) is a highly metastatic and lethal disease. In PDA, extracellular matrix (ECM) architectures, known as tumor-ass...

Machine Learning Prediction of Pancreatitis Risk With Antithyroid Drugs: A Nationwide Retrospective Observational Study.

BACKGROUND: In recent years, there has been increasing data showing that the risk of acute pancreatitis (AP) is increased in patients using methimazol...

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder.

BACKGROUND: Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to ...

Pathway Enrichment-Based Unsupervised Learning Identifies Novel Subtypes of Cancer-Associated Fibroblasts in Pancreatic Ductal Adenocarcinoma.

Existing single-cell clustering methods are based on gene expressions that are susceptible to dropout events in single-cell RNA sequencing (scRNA-seq)...

Intercept Cancer: Cancer Pre-Screening with Large Scale Healthcare Foundation Models

Cancer screening, leading to early detection, saves lives. Unfortunately, existing screening techniques require expensive and intrusive medical proc...